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bibliography.bib
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@ARTICLE{Chawla2020-hi,
title = "Critiqued coronavirus simulation gets thumbs up from
code-checking efforts",
author = "Chawla, Dalmeet Singh",
journal = "Nature",
publisher = "Nature Publishing Group",
month = jun,
year = 2020,
language = "en",
issn = "0028-0836",
doi = "10.1038/d41586-020-01685-y"
}
@ARTICLE{Gronenschild2012-pp,
title = "The effects of {FreeSurfer} version, workstation type, and
Macintosh operating system version on anatomical volume and
cortical thickness measurements",
author = "Gronenschild, Ed H B M and Habets, Petra and Jacobs, Heidi I L
and Mengelers, Ron and Rozendaal, Nico and van Os, Jim and
Marcelis, Machteld",
abstract = "FreeSurfer is a popular software package to measure cortical
thickness and volume of neuroanatomical structures. However,
little if any is known about measurement reliability across
various data processing conditions. Using a set of 30 anatomical
T1-weighted 3T MRI scans, we investigated the effects of data
processing variables such as FreeSurfer version (v4.3.1, v4.5.0,
and v5.0.0), workstation (Macintosh and Hewlett-Packard), and
Macintosh operating system version (OSX 10.5 and OSX 10.6).
Significant differences were revealed between FreeSurfer version
v5.0.0 and the two earlier versions. These differences were on
average 8.8 $\pm$ 6.6\% (range 1.3-64.0\%) (volume) and 2.8 $\pm$
1.3\% (1.1-7.7\%) (cortical thickness). About a factor two
smaller differences were detected between Macintosh and
Hewlett-Packard workstations and between OSX 10.5 and OSX 10.6.
The observed differences are similar in magnitude as effect sizes
reported in accuracy evaluations and neurodegenerative
studies.The main conclusion is that in the context of an ongoing
study, users are discouraged to update to a new major release of
either FreeSurfer or operating system or to switch to a different
type of workstation without repeating the analysis; results thus
give a quantitative support to successive recommendations stated
by FreeSurfer developers over the years. Moreover, in view of the
large and significant cross-version differences, it is concluded
that formal assessment of the accuracy of FreeSurfer is
desirable.",
journal = "PLoS One",
volume = 7,
number = 6,
pages = "e38234",
month = jun,
year = 2012,
language = "en",
issn = "1932-6203",
pmid = "22675527",
doi = "10.1371/journal.pone.0038234",
pmc = "PMC3365894"
}
@article{cert-2020-001,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-001},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@ARTICLE{Piccolo2020-lo,
title = "{ShinyLearner}: A containerized benchmarking tool for
machine-learning classification of tabular data",
author = "Piccolo, Stephen R and Lee, Terry J and Suh, Erica and Hill,
Kimball",
journal = "Gigascience",
volume = 9,
number = 4,
month = apr,
year = 2020,
keywords = "algorithm optimization; benchmark; classification; feature
selection; machine learning; model selection; software
containers; supervised learning",
language = "en",
issn = "2047-217X",
pmid = "32249316",
doi = "10.1093/gigascience/giaa026",
pmc = "PMC7131989"
}
@article{cert-2020-002,
author = {Stephen J. Eglen and Daniel N\"{u}st},
title = {{CODECHECK} Certificate 2020-002},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@ARTICLE{Hancock1992-mp,
title = "The principal components of natural images",
author = "Hancock, Peter J B and Baddeley, Roland J and Smith, Leslie S",
abstract = "A neural net was used to analyse samples of natural images and
text. For the natural images, components resemble derivatives of
Gaussian operators, similar to those found in visual cortex and
inferred from psychophysics. While the results from natural
images do not depend on scale, those from text images are highly
scale dependent. Convolution of one of the text components with
an original image shows that it is sensitive to inter-word gaps.",
journal = "Network: Computation in Neural Systems",
publisher = "Taylor \& Francis",
volume = 3,
number = 1,
pages = "61--70",
year = 1992,
eprint = "http://www.tandfonline.com/doi/pdf/10.1088/0954-898X\_3\_1\_008",
doi = "10.1088/0954-898X_3_1_008"
}
@article{cert-2020-003,
author = {Daniel N\"{u}st},
title = {{CODECHECK} Certificate 2020-003},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@ARTICLE{Hopfield1982-mz,
title = "Neural networks and physical systems with emergent collective
computational abilities",
author = "Hopfield, J J",
abstract = "Computational properties of use of biological organisms or to the
construction of computers can emerge as collective properties of
systems having a large number of simple equivalent components (or
neurons). The physical meaning of content-addressable memory is
described by an appropriate phase space flow of the state of a
system. A model of such a system is given, based on aspects of
neurobiology but readily adapted to integrated circuits. The
collective properties of this model produce a content-addressable
memory which correctly yields an entire memory from any subpart
of sufficient size. The algorithm for the time evolution of the
state of the system is based on asynchronous parallel processing.
Additional emergent collective properties include some capacity
for generalization, familiarity recognition, categorization,
error correction, and time sequence retention. The collective
properties are only weakly sensitive to details of the modeling
or the failure of individual devices.",
journal = "Proc. Natl. Acad. Sci. U. S. A.",
volume = 79,
number = 8,
pages = "2554--2558",
month = apr,
year = 1982,
language = "en",
issn = "0027-8424",
pmid = "6953413",
doi = "10.1073/pnas.79.8.2554",
pmc = "PMC346238"
}
@article{cert-2020-004,
author = {Daniel N\"{u}st},
title = {{CODECHECK} Certificate 2020-004},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@ARTICLE{Barto1983-rg,
title = "Neuronlike adaptive elements that can solve difficult learning
control problems",
author = "Barto, A G and Sutton, R S and Anderson, C W",
abstract = "It is shown how a system consisting of two neuronlike adaptive
elements can solve a difficult learning control problem. The task
is to balance a pole that is hinged to a movable cart by applying
forces to the cart's base. It is argued that the learning
problems faced by adaptive elements that are components of
adaptive networks are at least as difficult as this version of
the pole-balancing problem. The learning system consists of a
single associative search element (ASE) and a single adaptive
critic element (ACE). In the course of learning to balance the
pole, the ASE constructs associations between input and output by
searching under the influence of reinforcement feedback, and the
ACE constructs a more informative evaluation function than
reinforcement feedback alone can provide. The differences between
this approach and other attempts to solve problems using
neurolike elements are discussed, as is the relation of this work
to classical and instrumental conditioning in animal learning
studies and its possible implications for research in the
neurosciences.",
journal = "IEEE Trans. Syst. Man Cybern.",
volume = "SMC-13",
number = 5,
pages = "834--846",
month = sep,
year = 1983,
keywords = "adaptive control;learning systems;neural nets;neural
nets;adaptive control;neuronlike adaptive elements;learning
control problem;movable cart;associative search element;adaptive
critic element;animal learning studies;Adaptive
systems;Problem-solving;Training;Pattern
recognition;Neurons;Supervised learning;Biological neural
networks",
issn = "0018-9472, 2168-2909",
doi = "10.1109/TSMC.1983.6313077"
}
@article{cert-2020-005,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-005},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@article{larisch_re_2019,
title = {[{Re}] {Connectivity} reflects coding a model of voltage-based {STDP} with homeostasis},
volume = {5},
copyright = {Creative Commons Attribution 4.0 International, Open Access},
doi = {10.5281/ZENODO.3538217},
abstract = {Since the first description of spike-timing-dependent plasticity (STDP), different models of STDP has been published to reproduce different experimental findings. Clopath et al. (2010) introduced an STDP model which is able to reproduce the experimental findings of triplet studies. They implemented a homeostatic mechanism to control the level of generated LTD, based on the relationship between the average postsynaptic membrane potential and a reference value. With this voltage-based STDP rule, they reproduce a wide range of physiological experiments. We here present a reimplementation of the Clopath et al. (2010) learning rule in Python with the help of the neuro-simulator ANNarchy.},
number = {3},
journal = {ReScience C},
author = {Larisch, Rene},
month = nov,
year = {2019},
publisher = {Zenodo},
keywords = {Computational Neuroscience, Python}
}
@article{cert-2020-006,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-006},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@article{detorakis_re_2017,
title = {[{Re}] {A} {Generalized} {Linear} {Integrate}-{And}-{Fire} {Neural} {Model} {Produces} {Diverse} {Spiking} {Behaviors}},
volume = {3},
copyright = {Creative Commons Attribution 4.0, Open Access},
doi = {10.5281/ZENODO.1003214},
abstract = {A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors, ReScience 3(7), 2017},
number = {1},
journal = {ReScience C},
author = {Detorakis, Georgios},
month = oct,
year = {2017},
publisher = {Zenodo},
keywords = {generalized linear integrate-and-fire neuron, Python},
pages = {\#7}
}
@article{cert-2020-007,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-007},
year = {2020},
doi = {"TODO"},
journal = {Zenodo}
}
@article{hathway_re_2018,
title = {[{Re}] {Spike} {Timing} {Dependent} {Plasticity} {Finds} {The} {Start} {Of} {Repeating} {Patterns} {In} {Continuous} {Spike} {Trains}},
volume = {4},
copyright = {Creative Commons Attribution 4.0, Open Access},
doi = {10.5281/ZENODO.1327348},
abstract = {A reference implementation of Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains, Masquelier T, Guyonneau R, Thorpe SJ, PLoS ONE 3(1): e1377, 2008. https://doi.org/10.1371/journal.pone.0001377},
language = {en},
number = {1},
journal = {ReScience C},
author = {Hathway, Pamela and Goodman, Dan F. M.},
month = aug,
year = {2018},
publisher = {Zenodo},
keywords = {Brian, Python, Spatio-temporal spike pattern, STDP},
pages = {\#6}
}
@article{cert-2020-008,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-008},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@misc{davies-preprint-2020,
title = {Effects of non-pharmaceutical interventions on {COVID-19} cases,
deaths, and demand for hospital services in the {UK}: a
modelling study},
author = {Davies, Nicholas G and Kucharski, Adam J and Eggo, Rosalind M
and Gimma, Amy and {CMMID COVID-19 working group} and Edmunds, W John},
year = {2020},
month = {April},
url = {https://github.com/cmmid/cmmid.github.io/blob/master/topics/covid19/reports/uk_scenario_modelling_preprint_2020_04_01.pdf},
urldate = {2021-01-11}
}
@ARTICLE{Davies2020-vj,
title = "Effects of non-pharmaceutical interventions on {COVID-19} cases,
deaths, and demand for hospital services in the {UK}: a
modelling study",
author = "Davies, Nicholas G and Kucharski, Adam J and Eggo, Rosalind M
and Gimma, Amy and Edmunds, W John and Jombart, Thibaut and
O'Reilly, Kathleen and Endo, Akira and Hellewell, Joel and
Nightingale, Emily S and Quilty, Billy J and Jarvis, Christopher
I and Russell, Timothy W and Klepac, Petra and Bosse, Nikos I
and Funk, Sebastian and Abbott, Sam and Medley, Graham F and
Gibbs, Hamish and Pearson, Carl A B and Flasche, Stefan and Jit,
Mark and Clifford, Samuel and Prem, Kiesha and Diamond, Charlie
and Emery, Jon and Deol, Arminder K and Procter, Simon R and van
Zandvoort, Kevin and Sun, Yueqian Fiona and Munday, James D and
Rosello, Alicia and Auzenbergs, Megan and Knight, Gwen and
Houben, Rein M G J and Liu, Yang",
abstract = "BackgroundNon-pharmaceutical interventions have been implemented
to reduce transmission of severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2) in the UK. Projecting the size of an
unmitigated epidemic and the potential effect of different
control measures has been crucial to support evidence-based
policy making during the early stages of the epidemic. This
study assesses the potential impact of different control
measures for mitigating the burden of COVID-19 in the UK.",
journal = "The Lancet Public Health",
publisher = "Elsevier",
month = jun,
year = 2020,
issn = "2468-2667",
doi = "10.1016/S2468-2667(20)30133-X"
}
@article{cert-2020-009,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-009},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
% proper preprint https://doi.org/10.1101/2020.04.23.20077024, but checked before that
@misc{kucharski-preprint-2020,
title = {Effectiveness of isolation, testing, contact tracing and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study},
author = {Kucharski, Adam J and Klepac, Petra and Conlan, Andrew J. K. and Kissler, Stephen M. and Tang, Maria and Fry, Hannah and Gog, Julia R. and Edmunds, W. John and {CMMID COVID-19 working group}},
year = {2020},
month = {April},
url = {https://cmmid.github.io/topics/covid19/reports/bbc_contact_tracing.pdf},
urldate = {2021-01-11}
}
% codecheck mentioned in acknowledgements but not linked to
@article{kucharski_effectiveness_2020,
title = {Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of {SARS}-{CoV}-2 in different settings: a mathematical modelling study},
volume = {20},
issn = {1473-3099, 1474-4457},
shorttitle = {Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of {SARS}-{CoV}-2 in different settings},
doi = {10.1016/S1473-3099(20)30457-6},
abstract = {{\textless}h2{\textgreater}Summary{\textless}/h2{\textgreater}{\textless}h3{\textgreater}Background{\textless}/h3{\textgreater}{\textless}p{\textgreater}The isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures—including novel digital tracing approaches and less intensive physical distancing—might be required to reduce transmission. We aimed to estimate the reduction in transmission under different control measures across settings and how many contacts would be quarantined per day in different strategies for a given level of symptomatic case incidence.{\textless}/p{\textgreater}{\textless}h3{\textgreater}Methods{\textless}/h3{\textgreater}{\textless}p{\textgreater}For this mathematical modelling study, we used a model of individual-level transmission stratified by setting (household, work, school, or other) based on BBC Pandemic data from 40 162 UK participants. We simulated the effect of a range of different testing, isolation, tracing, and physical distancing scenarios. Under optimistic but plausible assumptions, we estimated reduction in the effective reproduction number and the number of contacts that would be newly quarantined each day under different strategies.{\textless}/p{\textgreater}{\textless}h3{\textgreater}Results{\textless}/h3{\textgreater}{\textless}p{\textgreater}We estimated that combined isolation and tracing strategies would reduce transmission more than mass testing or self-isolation alone: mean transmission reduction of 2\% for mass random testing of 5\% of the population each week, 29\% for self-isolation alone of symptomatic cases within the household, 35\% for self-isolation alone outside the household, 37\% for self-isolation plus household quarantine, 64\% for self-isolation and household quarantine with the addition of manual contact tracing of all contacts, 57\% with the addition of manual tracing of acquaintances only, and 47\% with the addition of app-based tracing only. If limits were placed on gatherings outside of home, school, or work, then manual contact tracing of acquaintances alone could have an effect on transmission reduction similar to that of detailed contact tracing. In a scenario where 1000 new symptomatic cases that met the definition to trigger contact tracing occurred per day, we estimated that, in most contact tracing strategies, 15 000–41 000 contacts would be newly quarantined each day.{\textless}/p{\textgreater}{\textless}h3{\textgreater}Interpretation{\textless}/h3{\textgreater}{\textless}p{\textgreater}Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimated that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number lower than 1 in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control of severe acute respiratory syndrome coronavirus 2 transmission.{\textless}/p{\textgreater}{\textless}h3{\textgreater}Funding{\textless}/h3{\textgreater}{\textless}p{\textgreater}Wellcome Trust, UK Engineering and Physical Sciences Research Council, European Commission, Royal Society, Medical Research Council.{\textless}/p{\textgreater}},
language = {English},
number = {10},
journal = {The Lancet Infectious Diseases},
author = {Kucharski, Adam J. and Klepac, Petra and Conlan, Andrew J. K. and Kissler, Stephen M. and Tang, Maria L. and Fry, Hannah and Gog, Julia R. and Edmunds, W. John and Emery, Jon C. and Medley, Graham and Munday, James D. and Russell, Timothy W. and Leclerc, Quentin J. and Diamond, Charlie and Procter, Simon R. and Gimma, Amy and Sun, Fiona Yueqian and Gibbs, Hamish P. and Rosello, Alicia and Zandvoort, Kevin van and Hué, Stéphane and Meakin, Sophie R. and Deol, Arminder K. and Knight, Gwen and Jombart, Thibaut and Foss, Anna M. and Bosse, Nikos I. and Atkins, Katherine E. and Quilty, Billy J. and Lowe, Rachel and Prem, Kiesha and Flasche, Stefan and Pearson, Carl A. B. and Houben, Rein M. G. J. and Nightingale, Emily S. and Endo, Akira and Tully, Damien C. and Liu, Yang and Villabona-Arenas, Julian and O'Reilly, Kathleen and Funk, Sebastian and Eggo, Rosalind M. and Jit, Mark and Rees, Eleanor M. and Hellewell, Joel and Clifford, Samuel and Jarvis, Christopher I. and Abbott, Sam and Auzenbergs, Megan and Davies, Nicholas G. and Simons, David},
month = oct,
year = {2020},
pmid = {32559451},
publisher = {Elsevier},
pages = {1151--1160}
}
@article{cert-2020-010,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-010},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@techreport{ferguson_report_2020,
title = {Report 9: {Impact} of non-pharmaceutical interventions ({NPIs}) to reduce {COVID19} mortality and healthcare demand},
copyright = {© 2020. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/).},
abstract = {The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission. Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option. We show that in the UK and US context, suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and university closures, though it should be recognised that such closures may have negative impacts on health systems due to increased absenteeism. The major challenge of suppression is that this type of intensive intervention package – or something equivalently effective at reducing transmission – will need to be maintained until a vaccine becomes available (potentially 18 months or more) – given that we predict that transmission will quickly rebound if interventions are relaxed. We show that intermittent social distancing – triggered by trends in disease surveillance – may allow interventions to be relaxed temporarily in relative short time windows, but measures will need to be reintroduced if or when case numbers rebound. Last, while experience in China and now South Korea show that suppression is possible in the short term, it remains to be seen whether it is possible long-term, and whether the social and economic costs of the interventions adopted thus far can be reduced.},
language = {en-US-GB},
author = {Ferguson, N. and Laydon, D. and Nedjati Gilani, G. and Imai, N. and Ainslie, K. and Baguelin, M. and Bhatia, S. and Boonyasiri, A. and Cucunuba Perez, Z. and Cuomo-Dannenburg, G. and Dighe, A. and Dorigatti, I. and Fu, H. and Gaythorpe, K. and Green, W. and Hamlet, A. and Hinsley, W. and Okell, L. and Van Elsland, S. and Thompson, H. and Verity, R. and Volz, E. and Wang, H. and Wang, Y. and Walker, P. and Walters, C. and Winskill, P. and Whittaker, C. and Donnelly, C. and Riley, S. and Ghani, A.},
month = mar,
year = {2020},
institution = {{Imperial College London}},
doi = {10.25561/77482}
}
@article{cert-2020-011,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-011},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@article{flaxman_estimating_2020,
title = {Estimating the effects of non-pharmaceutical interventions on {COVID}-19 in {Europe}},
volume = {584},
copyright = {2020 The Author(s), under exclusive licence to Springer Nature Limited},
issn = {1476-4687},
doi = {10.1038/s41586-020-2405-7},
abstract = {Following the detection of the new coronavirus1 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics of coronavirus disease 2019 (COVID-19). In response, many European countries have implemented non-pharmaceutical interventions, such as the closure of schools and national lockdowns. Here we study the effect of major interventions across 11 European countries for the period from the start of the COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks previously, allowing for the time lag between infection and death. We use partial pooling of information between countries, with both individual and shared effects on the time-varying reproduction number (Rt). Pooling allows for more information to be used, helps to overcome idiosyncrasies in the data and enables more-timely estimates. Our model relies on fixed estimates of some epidemiological parameters (such as the infection fatality rate), does not include importation or subnational variation and assumes that changes in Rt are an immediate response to interventions rather than gradual changes in behaviour. Amidst the ongoing pandemic, we rely on death data that are incomplete, show systematic biases in reporting and are subject to future consolidation. We estimate that—for all of the countries we consider here—current interventions have been sufficient to drive Rt below 1 (probability Rt {\textless} 1.0 is greater than 99\%) and achieve control of the epidemic. We estimate that across all 11 countries combined, between 12 and 15 million individuals were infected with SARS-CoV-2 up to 4 May 2020, representing between 3.2\% and 4.0\% of the population. Our results show that major non-pharmaceutical interventions—and lockdowns in particular—have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.},
language = {en},
number = {7820},
journal = {Nature},
author = {Flaxman, Seth and Mishra, Swapnil and Gandy, Axel and Unwin, H. Juliette T. and Mellan, Thomas A. and Coupland, Helen and Whittaker, Charles and Zhu, Harrison and Berah, Tresnia and Eaton, Jeffrey W. and Monod, Mélodie and Ghani, Azra C. and Donnelly, Christl A. and Riley, Steven and Vollmer, Michaela A. C. and Ferguson, Neil M. and Okell, Lucy C. and Bhatt, Samir},
month = aug,
year = {2020},
publisher = {Nature Publishing Group},
pages = {257--261}
}
@article{cert-2020-012,
author = {Stephen J. Eglen},
title = {{CODECHECK} Certificate 2020-012},
year = 2020,
doi = "10.5281/zenodo.3893617",
journal = {Zenodo}
}
@techreport{unwin_report_2020,
title = {Report 23: {State}-level tracking of {COVID}-19 in the {United} {States}},
shorttitle = {Report 23},
abstract = {our estimates show that the percentage of individuals that have been infected is 4.1\% [3.7\%-4.5\%], with wide variation between states. For all states, even for the worst affected states, we estimate that less than a quarter of the population has been infected; in New York, for example, we estimate that 16.6\% [12.8\%-21.6\%] of individuals have been infected to date. Our attack rates for New York are in line with those from recent serological studies [1] broadly supporting our choice of infection fatality rate. There is variation in the initial reproduction number, which is likely due to a range of factors; we find a strong association between the initial reproduction number with both population density (measured at the state level) and the chronological date when 10 cumulative deaths occurred (a crude estimate of the date of locally sustained transmission). Our estimates suggest that the epidemic is not under control in much of the US: as of 17 May 2020 the reproduction number is above the critical threshold (1.0) in 24 [95\% CI: 20-30] states. Higher reproduction numbers are geographically clustered in the South and Midwest, where epidemics are still developing, while we estimate lower reproduction numbers in states that have already suffered high COVID-19 mortality (such as the Northeast). These estimates suggest that caution must be taken in loosening current restrictions if effective additional measures are not put in place. We predict that increased mobility following relaxation of social distancing will lead to resurgence of transmission, keeping all else constant. We predict that deaths over the next two-month period could exceed current cumulative deaths by greater than two-fold, if the relationship between mobility and transmission remains unchanged. Our results suggest that factors modulating transmission such as rapid testing, contact tracing and behavioural precautions are crucial to offset the rise of transmission associated with loosening of social distancing. Overall, we show that while all US states have substantially reduced their reproduction numbers, there is little evidence that any states are approaching herd immunity and thus the epidemic is close to over in any state.},
language = {en-US-GB},
author = {Unwin, H. and Mishra, S. and Bradley, V. C. and Gandy, A. and Vollmer, M. and Mellan, T. and Coupland, H. and Ainslie, K. and Whittaker, C. and Ish-Horowicz, J. and Filippi, S. and Xi, X. and Monod, M. and Ratmann, O. and Hutchinson, M. and Valka, F. and Zhu, H. and Hawryluk, I. and Milton, P. and Baguelin, M. and Boonyasiri, A. and Brazeau, N. and Cattarino, L. and Charles, G. and Cooper, L. and Cucunuba Perez, Z. and Cuomo-Dannenburg, G. and Djaafara, A. and Dorigatti, I. and Eales, O. and Eaton, J. and Van Elsland, S. and Fitzjohn, R. and Gaythorpe, K. and Green, W. and Hallett, T. and Hinsley, W. and Imai, N. and Jeffrey, B. and Knock, E. and Laydon, D. and Lees, J. and Nedjati Gilani, G. and Nouvellet, P. and Okell, L. and Ower, A. and Parag, K. and Siveroni, I. and Thompson, H. and Verity, R. and Walker, P. and Walters, C. and Wang, Y. and Watson, O. and Whittles, L. and Ghani, A. and Ferguson, N. and Riley, S. and Donnelly, C. and Bhatt, S. and Flaxman, S.},
month = may,
year = {2020},
institution = {{Imperial College London}},
doi = {10.25561/79231}
}
@article{unwin_state-level_2020,
title = {State-level tracking of {COVID}-19 in the {United} {States}},
volume = {11},
copyright = {2020 The Author(s)},
issn = {2041-1723},
doi = {10.1038/s41467-020-19652-6},
abstract = {As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that Rt was only below one in 23 states on 1st June. We also estimate that 3.7\% [3.4\%–4.0\%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01\% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.},
language = {en},
number = {1},
journal = {Nature Communications},
author = {Unwin, H. Juliette T. and Mishra, Swapnil and Bradley, Valerie C. and Gandy, Axel and Mellan, Thomas A. and Coupland, Helen and Ish-Horowicz, Jonathan and Vollmer, Michaela A. C. and Whittaker, Charles and Filippi, Sarah L. and Xi, Xiaoyue and Monod, Mélodie and Ratmann, Oliver and Hutchinson, Michael and Valka, Fabian and Zhu, Harrison and Hawryluk, Iwona and Milton, Philip and Ainslie, Kylie E. C. and Baguelin, Marc and Boonyasiri, Adhiratha and Brazeau, Nick F. and Cattarino, Lorenzo and Cucunuba, Zulma and Cuomo-Dannenburg, Gina and Dorigatti, Ilaria and Eales, Oliver D. and Eaton, Jeffrey W. and van Elsland, Sabine L. and FitzJohn, Richard G. and Gaythorpe, Katy A. M. and Green, William and Hinsley, Wes and Jeffrey, Benjamin and Knock, Edward and Laydon, Daniel J. and Lees, John and Nedjati-Gilani, Gemma and Nouvellet, Pierre and Okell, Lucy and Parag, Kris V. and Siveroni, Igor and Thompson, Hayley A. and Walker, Patrick and Walters, Caroline E. and Watson, Oliver J. and Whittles, Lilith K. and Ghani, Azra C. and Ferguson, Neil M. and Riley, Steven and Donnelly, Christl A. and Bhatt, Samir and Flaxman, Seth},
month = dec,
year = {2020},
publisher = {Nature Publishing Group},
pages = {6189}
}
@article{cert-2020-013,
author = {Iain Davies},
title = {{CODECHECK} Certificate 2020-013},
month = jul,
year = 2020,
publisher = {Zenodo},
journal = {Zenodo},
doi = {10.5281/zenodo.3947959}
}
@article{Spitschan2020.06.02.129502,
title = {Rest-activity cycles and melatonin phase angle of circadian entrainment in people without cone-mediated vision},
doi = {10.1101/2020.06.02.129502},
journal = {bioRxiv},
author = {Spitschan, Manuel and Garbazza, Corrado and Kohl, Susanne and Cajochen, Christian},
year = {2020},
publisher = {Cold Spring Harbor Laboratory}
}
@article{cert-2020-014,
author = {Iain Davies},
title = {{CODECHECK} Certificate 2020-014},
month = jul,
year = 2020,
journal = {Zenodo},
doi = {10.5281/zenodo.3967326}
}
@article{Sadeh2020,
doi = {10.7554/elife.52757},
year = {2020},
month = feb,
publisher = {{eLife} Sciences Publications, Ltd},
volume = {9},
issn = {2050-084X},
editor = {Palmer, Stephanie and Frank, Michael J},
pages = {e52757},
author = {Sadra Sadeh and Claudia Clopath},
title = {Patterned perturbation of inhibition can reveal the dynamical structure of neural processing},
journal = {{eLife}}
}
@article{cert-2020-015,
author = {Iain Davies},
title = {{CODECHECK} Certificate 2020-015},
month = aug,
year = 2020,
journal = {Zenodo},
doi = {10.5281/zenodo.3978402},
}
@article{Liou2020,
doi = {10.7554/elife.50927},
year = {2020},
month = mar,
publisher = {{eLife} Sciences Publications, Ltd},
volume = {9},
pages = {e50927},
author = {Jyun-you Liou and Elliot H Smith and Lisa M Bateman and Samuel L Bruce and Guy M McKhann and Robert R Goodman and Ronald G Emerson and Catherine A Schevon and LF Abbott},
title = {A model for focal seizure onset, propagation, evolution, and progression},
issn = {2050-084X},
editor = {Calabrese, Ronald L and Ramirez, Jan-Marino and Ramirez, Jan-Marino and Staley, Kevin and Khambhati, AN},
journal = {{eLife}}
}
@article{cert-2020-016,
author = {Daniel N\"ust},
title = {{CODECHECK} Certificate 2020-016},
month = jun,
year = 2020,
journal = {Zenodo},
doi = {10.5281/zenodo.3981253}
}
@article{Brunsdon2020,
doi = {10.1007/s10109-020-00334-2},
year = {2020},
month = aug,
publisher = {Springer Science and Business Media {LLC}},
author = {Chris Brunsdon and Alexis Comber},
title = {Opening practice: supporting reproducibility and critical spatial data science},
journal = {Journal of Geographical Systems}
}
@article{cert-2020-017,
author = {Daniel N\"ust},
title = {{CODECHECK} Certificate 2020-017},
month = aug,
year = 2020,
journal = {Zenodo},
doi = {10.5281/zenodo.4003848}
}
@article{Bivand2020,
doi = {10.1007/s10109-020-00336-0},
year = {2020},
publisher = {Springer Science and Business Media {LLC}},
author = {Bivand, Roger S.},
title = {Progress in the R ecosystem for representing and handling spatialdata},
journal = {Journal of Geographical Systems}
}
@article{cert-2020-018,
doi = {10.17605/OSF.IO/ZTC7M},
author = {N\"{u}st, Daniel},
title = {Reproducibility review of: Integrating cellular automata and discrete global grid systems: a case study into wildfire modelling},
journal = {Open Science Framework},
year = {2020}
}
@article{Hojati2020,
doi = {10.5194/agile-giss-1-6-2020},
year = {2020},
month = jul,
publisher = {Copernicus {GmbH}},
volume = {1},
pages = {1--23},
author = {Majid Hojati and Colin Robertson},
title = {Integrating cellular automata and discrete global grid systems: a case study into wildfire modelling},
journal = {{AGILE}: {GIScience} Series}
}
@article{cert-2020-019,
doi = {10.17605/OSF.IO/5SVMT},
author = {N\"{u}st, Daniel and Granell, Carlos},
title = {Reproducibility review of: What to do in the Meantime: A Service Coverage Analysis for Parked Autonomous Vehicles},
journal = {Open Science Framework},
year = {2020}
}
@article{Illium2020,
doi = {10.5194/agile-giss-1-7-2020},
year = {2020},
month = jul,
publisher = {Copernicus {GmbH}},
volume = {1},
pages = {1--15},
author = {Steffen Illium and Philipp Andreas Friese and Robert M\"{u}ller and Sebastian Feld},
title = {What to do in the Meantime: A Service Coverage Analysis for Parked Autonomous Vehicles},
journal = {{AGILE}: {GIScience} Series}
}
@article{cert-2020-020,
doi = {10.17605/OSF.IO/7TWR2},
author = {N\"{u}st, Daniel and Ostermann, Frank},
title = {Reproducibility review of: Window Operators for Processing Spatio-Temporal Data Streams on Unmanned Vehicles},
journal = {Open Science Framework},
year = {2020}
}
@article{Werner2020,
doi = {10.5194/agile-giss-1-21-2020},
year = {2020},
month = jul,
publisher = {Copernicus {GmbH}},
volume = {1},
pages = {1--23},
author = {Tobias Werner and Thomas Brinkhoff},
title = {Window Operators for Processing Spatio-Temporal Data Streams on Unmanned Vehicles},
journal = {{AGILE}: {GIScience} Series}
}
@article{cert-2020-021,
doi = {10.17605/OSF.IO/SUWPJ},
author = {Ostermann, Frank and N\"{u}st, Daniel},
title = {Reproducibility Review of: Comparing supervised learning algorithms for Spatial Nominal Entity recognition},
journal = {Open Science Framework},
year = {2020}
}
@article{Medad2020,
doi = {10.5194/agile-giss-1-15-2020},
year = {2020},
month = jul,
publisher = {Copernicus {GmbH}},
volume = {1},
pages = {1--18},
author = {Amine Medad and Mauro Gaio and Ludovic Moncla and S{\'{e}}bastien Musti{\`{e}}re and Yannick Le Nir},
title = {Comparing supervised learning algorithms for Spatial Nominal Entity recognition},
journal = {{AGILE}: {GIScience} Series}
}
@article{cert-2020-022,
doi = {10.17605/OSF.IO/7XRQG},
author = {N\"{u}st, Daniel},
title = {Reproducibility review of: Extracting interrogative intents and concepts from geo-analytic questions},
journal = {Open Science Framework},
year = {2020}
}
@article{Xu2020,
doi = {10.5194/agile-giss-1-23-2020},
year = {2020},
month = jul,
publisher = {Copernicus {GmbH}},
volume = {1},
pages = {1--21},
author = {Haiqi Xu and Ehsan Hamzei and Enkhbold Nyamsuren and Han Kruiger and Stephan Winter and Martin Tomko and Simon Scheider},
title = {Extracting interrogative intents and concepts from geo-analytic questions},
journal = {{AGILE}: {GIScience} Series}
}
@article{cert-2020-023,
doi = {10.17605/OSF.IO/XS5YR},
author = {Ostermann, Frank and N\"{u}st, Daniel},
title = {Reproducibility review of: Tracking Hurricane Dorian in GDELT and Twitter},
journal = {Open Science Framework},
year = {2020}
}
@article{Owuor2020,
doi = {10.5194/agile-giss-1-19-2020},
year = {2020},
month = jul,
publisher = {Copernicus {GmbH}},
volume = {1},
pages = {1--18},
author = {Innocensia Owuor and Hartwig H. Hochmair and Sreten Cvetojevic},
title = {Tracking Hurricane Dorian in {GDELT} and Twitter},
journal = {{AGILE}: {GIScience} Series}
}
@ARTICLE{Barnes2010-iv,
title = "Publish your computer code: it is good enough",
author = "Barnes, Nick",
journal = "Nature",
volume = 467,
number = 7317,
pages = "753",
month = oct,
year = 2010,
issn = "0028-0836, 1476-4687",
pmid = "20944687",
doi = "10.1038/467753a"
}
@article{sandve_ten_2013,
title = {Ten {Simple} {Rules} for {Reproducible} {Computational} {Research}},
volume = {9},
doi = {10.1371/journal.pcbi.1003285},
number = {10},
journal = {PLoS Comput Biol},
author = {Sandve, Geir Kjetil and Nekrutenko, Anton and Taylor, James and Hovig, Eivind},
year = {2013},
keywords = {Archives, Computer and information sciences, Computer applications, Habits, Replication studies, Reproducibility, Sequence analysis, Source code},
pages = {e1003285}
}
@article{rule_ten_2019,
title = {Ten simple rules for writing and sharing computational analyses in {Jupyter} {Notebooks}},
volume = {15},
issn = {1553-7358},
doi = {10.1371/journal.pcbi.1007007},
language = {en},
number = {7},
journal = {PLOS Computational Biology},
author = {Rule, Adam and Birmingham, Amanda and Zuniga, Cristal and Altintas, Ilkay and Huang, Shih-Cheng and Knight, Rob and Moshiri, Niema and Nguyen, Mai H. and Rosenthal, Sara Brin and Pérez, Fernando and Rose, Peter W.},
year = {2019},
keywords = {Reproducibility, Data processing, Computer and information sciences, Metadata, Analysts, Computer hardware, Ecosystems, Graphical user interfaces},
pages = {e1007007}
}
@article{peng_reproducible_2011,
title = {Reproducible {Research} in {Computational} {Science}},
volume = {334},
copyright = {Copyright © 2011, American Association for the Advancement of Science},
issn = {0036-8075, 1095-9203},
doi = {10.1126/science.1213847},
abstract = {Computational science has led to exciting new developments, but the nature of the work has exposed limitations in our ability to evaluate published findings. Reproducibility has the potential to serve as a minimum standard for judging scientific claims when full independent replication of a study is not possible.},
language = {en},
number = {6060},
journal = {Science},
author = {Peng, Roger D.},
year = {2011},
pmid = {22144613},
pages = {1226--1227}
}
@article{barba_terminologies_2018,
title = {Terminologies for {Reproducible} {Research}},
url = {http://arxiv.org/abs/1802.03311},
abstract = {Reproducible research---by its many names---has come to be regarded as a key concern across disciplines and stakeholder groups. Funding agencies and journals, professional societies and even mass media are paying attention, often focusing on the so-called "crisis" of reproducibility. One big problem keeps coming up among those seeking to tackle the issue: different groups are using terminologies in utter contradiction with each other. Looking at a broad sample of publications in different fields, we can classify their terminology via decision tree: they either, A---make no distinction between the words reproduce and replicate, or B---use them distinctly. If B, then they are commonly divided in two camps. In a spectrum of concerns that starts at a minimum standard of "same data+same methods=same results," to "new data and/or new methods in an independent study=same findings," group 1 calls the minimum standard reproduce, while group 2 calls it replicate. This direct swap of the two terms aggravates an already weighty issue. By attempting to inventory the terminologies across disciplines, I hope that some patterns will emerge to help us resolve the contradictions.},
journal = {arXiv:1802.03311 [cs]},
author = {Barba, Lorena A.},
year = {2018},
keywords = {Computer Science - Digital Libraries}
}
@article{chen_open_2019,
title = {Open is not enough},
volume = {15},
copyright = {2018 Springer Nature Limited},
issn = {1745-2481},
doi = {10.1038/s41567-018-0342-2},
abstract = {The solutions adopted by the high-energy physics community to foster reproducible research are examples of best practices that could be embraced more widely. This first experience suggests that reproducibility requires going beyond openness.},
language = {En},
number = {2},
journal = {Nature Physics},
author = {Chen, Xiaoli and Dallmeier-Tiessen, S{\"u}nje and Dasler, Robin and Feger, Sebastian and Fokianos, Pamfilos and Gonzalez, Jose Benito and Hirvonsalo, Harri and Kousidis, Dinos and Lavasa, Artemis and Mele, Salvatore and Rodríguez, Diego and \v{S}imko, Tibor and Smith, Tim and Trisovic, Ana and Trzcinska, Anna and Tsanaktsidis, Ioannis and Zimmermann, Markus and Cranmer, Kyle and Heinrich, Lukas and Watts, Gordon and Hildreth, Michael and Iglesias, Lara Lloret and Lassila-Perini, Kati and Neubert, Sebastian},
year = {2019},
pages = {113}
}
@article{schonbrodt_training_2019,
title = {Training students for the {Open} {Science} future},
volume = {3},
issn = {2397-3374},
doi = {10.1038/s41562-019-0726-z},
language = {en},
number = {10},
journal = {Nature Human Behaviour},
author = {Sch{\"o}nbrodt, Felix},
year = {2019},
pages = {1031--1031}
}
@article{piwowar_altmetrics:_2013,
title = {Altmetrics: {Value} all research products},
volume = {493},
copyright = {2013 Nature Publishing Group},
issn = {1476-4687},
shorttitle = {Altmetrics},
doi = {10.1038/493159a},
abstract = {A new funding policy by the US National Science Foundation represents a sea-change in how researchers are evaluated, says Heather Piwowar.},
language = {en},
journal = {Nature},
author = {Piwowar, Heather},
year = {2013},
pages = {159}
}
@article{donoho_invitation_2010,
title = {An invitation to reproducible computational research},
volume = {11},
issn = {1465-4644},
doi = {10.1093/biostatistics/kxq028},
abstract = {I am genuinely thrilled to see Biostatistics make a formal venture into computational reproducibility, and I congratulate the editors of Biostatistics on taking},
language = {en},
number = {3},
journal = {Biostatistics},
author = {Donoho, David L.},
year = {2010},
pages = {385--388}
}
@incollection{claerbout_electronic_1992,
series = {{SEG} {Technical} {Program} {Expanded} {Abstracts}},
title = {Electronic documents give reproducible research a new meaning},
doi = {10.1190/1.1822162},
booktitle = {{SEG} {Technical} {Program} {Expanded} {Abstracts} 1992},
publisher = {Society of Exploration Geophysicists},
author = {Claerbout, J. and Karrenbach, M.},
year = {1992},
pages = {601--604}
}
@article{markowetz_five_2015,
title = {Five selfish reasons to work reproducibly},
volume = {16},
issn = {1474-760X},
doi = {10.1186/s13059-015-0850-7},
abstract = {And so, my fellow scientists: ask not what you can do for reproducibility; ask what reproducibility can do for you! Here, I present five reasons why working reproducibly pays off in the long run and is in the self-interest of every ambitious, career-oriented scientist.},
journal = {Genome Biology},
author = {Markowetz, Florian},
year = {2015},
keywords = {Reproducibility, Scientific career},
pages = {274}
}
@article{gentleman_statistical_2007,
title = {Statistical {Analyses} and {Reproducible} {Research}},
volume = {16},
issn = {1061-8600},
doi = {10.1198/106186007X178663},
abstract = {It is important, if not essential, to integrate the computations and code used in data analyses, methodological descriptions, simulations, and so on with the documents that describe and rely on them. This integration allows readers to both verify and adapt the claims in the documents. Authors can easily reproduce the results in the future, and they can present the document's contents in a different medium, for example, with interactive controls. This article describes a software framework for both authoring and distributing these integrated, dynamic documents that contain text, code, data, and any auxiliary content needed to recreate the computations. The documents are dynamic in that the contents---including figures, tables, and so on---can be recalculated each time a view of the document is generated. Our model treats a dynamic document as a master or “source” document from which one can generate different views in the form of traditional, derived documents for different audiences.We introduce the concept of a compendium as a container for one or more dynamic documents and the different elements needed when processing them, such as code and data. The compendium serves as a means for distributing, managing, and updating the collection.The step from disseminating analyses via a compendium to reproducible research is a small one. By reproducible research, we mean research papers with accompanying software tools that allow the reader to directly reproduce the results and employ the computational methods that are presented in the research paper. Some of the issues involved in paradigms for the production, distribution, and use of such reproducible research are discussed.},
number = {1},
journal = {Journal of Computational and Graphical Statistics},
author = {Gentleman, Robert and Lang, Duncan Temple},
year = {2007},
pages = {1--23}
}
@article{boettiger_introduction_2015,
title = {An {Introduction} to {Docker} for {Reproducible} {Research}},
volume = {49},
issn = {0163-5980},
doi = {10.1145/2723872.2723882},
abstract = {As computational work becomes more and more integral to many aspects of scientific research, computational reproducibility has become an issue of increasing importance to computer systems researchers and domain scientists alike. Though computational reproducibility seems more straight forward than replicating physical experiments, the complex and rapidly changing nature of computer environments makes being able to reproduce and extend such work a serious challenge. In this paper, I explore common reasons that code developed for one research project cannot be successfully executed or extended by subsequent researchers. I review current approaches to these issues, including virtual machines and workflow systems, and their limitations. I then examine how the popular emerging technology Docker combines several areas from systems research - such as operating system virtualization, cross-platform portability, modular re-usable elements, versioning, and a 'DevOps' philosophy, to address these challenges. I illustrate this with several examples of Docker use with a focus on the R statistical environment.},
number = {1},
journal = {SIGOPS Oper. Syst. Rev.},
author = {Boettiger, Carl},
year = {2015},
keywords = {Computer Science - Software Engineering},
pages = {71--79}
}
@article{howe_virtual_2012,
title = {Virtual {Appliances}, {Cloud} {Computing}, and {Reproducible} {Research}},
volume = {14},
issn = {1521-9615},
doi = {10.1109/MCSE.2012.62},
abstract = {As science becomes increasingly computational, reproducibility has become increasingly difficult, perhaps surprisingly. In many contexts, virtualization and cloud computing can mitigate the issues involved without significant overhead to the researcher, enabling the next generation of rigorous and reproducible computational science.},
number = {4},
journal = {Computing in Science Engineering},
author = {Howe, B.},
year = {2012},
keywords = {case studies in scientific applications, Cloud computing, context awareness, Documentation, Information Retrieval, Information Storage and Retrieval, Reproducibility of results, reproducible results, research and development, Scientific computing, services computing, Virtual machining},
pages = {36--41}
}
@article{kurtzer_singularity:_2017,
title = {Singularity: {Scientific} containers for mobility of compute},
volume = {12},
issn = {1932-6203},
shorttitle = {Singularity},
doi = {10.1371/journal.pone.0177459},
abstract = {Here we present Singularity, software developed to bring containers and reproducibility to scientific computing. Using Singularity containers, developers can work in reproducible environments of their choosing and design, and these complete environments can easily be copied and executed on other platforms. Singularity is an open source initiative that harnesses the expertise of system and software engineers and researchers alike, and integrates seamlessly into common workflows for both of these groups. As its primary use case, Singularity brings mobility of computing to both users and HPC centers, providing a secure means to capture and distribute software and compute environments. This ability to create and deploy reproducible environments across these centers, a previously unmet need, makes Singularity a game changing development for computational science.},
number = {5},
journal = {PLOS ONE},
author = {Kurtzer, Gregory M. and Sochat, Vanessa and Bauer, Michael W.},
year = {2017},
keywords = {Computer software, Operating Systems, software development, Open source software, Software tools, Research validity, Tar, Software design},
pages = {e0177459}
}
@article{knuth_literate_1984,
title = {Literate {Programming}},
volume = {27},
issn = {0010-4620},
doi = {10.1093/comjnl/27.2.97},
number = {2},
journal = {Comput. J.},
author = {Knuth, Donald E.},
year = {1984},
pages = {97--111}
}
@misc{marwick_how_2015,
title = {How computers broke science – and what we can do to fix it},
copyright = {Copyright © 2010–2019, The Conversation Trust (UK) Limited},
url = {http://theconversation.com/how-computers-broke-science-and-what-we-can-do-to-fix-it-49938},
abstract = {Virtually every researcher relies on computers to collect or analyze data. But when computers are opaque black boxes that manipulate data, it's impossible to replicate studies – a core value for science.},
language = {en},
urldate = {2017-07-05},
journal = {The Conversation},
author = {Marwick, Ben},
year = {2015}
}
@article{eglen_recent_2018,
title = {Recent developments in scholarly publishing to improve research practices in the life sciences},
volume = {2},
copyright = {© 2018 The Author(s). https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and the Royal Society of Biology and distributed under the Creative Commons Attribution License 4.0 (CC BY-NC-ND).},
issn = {2397-8554, 2397-8562},
doi = {10.1042/ETLS20180172},
abstract = {We outline recent developments in scholarly publishing that we think will improve the working environment and career prospects for life scientists. Most prominently, we discuss two key developments. (1) Life scientists are now embracing a preprint culture leading to rapid dissemination of research findings. (2) We outline steps to overcome the reproducibility crisis. We also briefly describe other innovations in scholarly publishing, along with changes to open access mandates from funding agencies.},
language = {en},
number = {6},
journal = {Emerging Topics in Life Sciences},
author = {Eglen, Stephen J. and Mounce, Ross and Gatto, Laurent and Currie, Adrian M. and Nobis, Yvonne},
year = {2018},
pages = {775--778}
}
@article{fanelli_opinion:_2018,
title = {Opinion: {Is} science really facing a reproducibility crisis, and do we need it to?},
copyright = {© 2018 . Published under the PNAS license.},
issn = {0027-8424, 1091-6490},
shorttitle = {Opinion},
doi = {10.1073/pnas.1708272114},
abstract = {Efforts to improve the reproducibility and integrity of science are typically justified by a narrative of crisis, according to which most published results are unreliable due to growing problems with research and publication practices. This article provides an overview of recent evidence suggesting that this narrative is mistaken, and argues that a narrative of epochal changes and empowerment of scientists would be more accurate, inspiring, and compelling.},
language = {en},
journal = {Proceedings of the National Academy of Sciences},
author = {Fanelli, Daniele},
year = {2018},
pmid = {29531051},
keywords = {reproducible research, bias, crisis, integrity, misconduct},
pages = {201708272}
}
@article{eglen_toward_2017,
title = {Toward standard practices for sharing computer code and programs in neuroscience},
volume = {20},
copyright = {2017 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
issn = {1546-1726},
doi = {10.1038/nn.4550},
abstract = {Computational techniques are central in many areas of neuroscience and are relatively easy to share. This paper describes why computer programs underlying scientific publications should be shared and lists simple steps for sharing. Together with ongoing efforts in data sharing, this should aid reproducibility of research.},
language = {en},
number = {6},
journal = {Nature Neuroscience},
author = {Eglen, Stephen J. and Marwick, Ben and Halchenko, Yaroslav O. and Hanke, Michael and Sufi, Shoaib and Gleeson, Padraig and Silver, R. Angus and Davison, Andrew P. and Lanyon, Linda and Abrams, Mathew and Wachtler, Thomas and Willshaw, David J. and Pouzat, Christophe and Poline, Jean-Baptiste},
year = {2017},
pages = {770--773}
}
@article{kluyver_jupyter_2016,
title = {Jupyter {Notebooks} - a publishing format for reproducible computational workflows},
doi = {10.3233/978-1-61499-649-1-87},
abstract = {It is increasingly necessary for researchers in all fields to write computer code, and in order to reproduce research results, it is important that this code is published. We present Jupyter notebooks, a document format for publishing code, results and explanations in a form that is both readable and executable. We discuss various tools and use cases for notebook documents.},
journal = {Positioning and Power in Academic Publishing: Players, Agents and Agendas},
author = {Kluyver, Thomas and Ragan-Kelley, Benjamin and Pérez, Fernando and Granger, Brian and Bussonier, Matthias and Frederic, Jonathan and Kelley, Kyle and Hamrick, Jessica and Grout, Jason and Corlay, Sylvan and Ivanov, Paul and Avila, Damián and Abdallan, Safia and Willing, Carol and Jupyter Development Team},
year = {2016},
pages = {87--90}
}
@article{perignon_certify_2019,
title = {Certify reproducibility with confidential data},
volume = {365},
copyright = {Copyright © 2019, American Association for the Advancement of Science. http://www.sciencemag.org/about/science-licenses-journal-article-reuseThis is an article distributed under the terms of the Science Journals Default License.},
issn = {0036-8075, 1095-9203},
doi = {10.1126/science.aaw2825},
abstract = {A trusted third party certifies that results reproduce
A trusted third party certifies that results reproduce},
language = {en},
number = {6449},
journal = {Science},
author = {Pérignon, Christophe and Gadouche, Kamel and Hurlin, Christophe and Silberman, Roxane and Debonnel, Eric},
year = {2019},
pmid = {31296759},
pages = {127--128}
}
@article{tennant_ten_2019,
title = {Ten {Hot} {Topics} around {Scholarly} {Publishing}},
volume = {7},
copyright = {http://creativecommons.org/licenses/by/3.0/},
doi = {10.3390/publications7020034},
abstract = {The changing world of scholarly communication and the emerging new wave of \‘Open Science\’ or \‘Open Research\’ has brought to light a number of controversial and hotly debated topics. Evidence-based rational debate is regularly drowned out by misinformed or exaggerated rhetoric, which does not benefit the evolving system of scholarly communication. This article aims to provide a baseline evidence framework for ten of the most contested topics, in order to help frame and move forward discussions, practices, and policies. We address issues around preprints and scooping, the practice of copyright transfer, the function of peer review, predatory publishers, and the legitimacy of \‘global\’ databases. These arguments and data will be a powerful tool against misinformation across wider academic research, policy and practice, and will inform changes within the rapidly evolving scholarly publishing system.},
language = {en},
number = {2},
journal = {Publications},
author = {Tennant, Jonathan P. and Crane, Harry and Crick, Tom and Davila, Jacinto and Enkhbayar, Asura and Havemann, Johanna and Kramer, Bianca and Martin, Ryan and Masuzzo, Paola and Nobes, Andy and Rice, Curt and Rivera-López, Bárbara and Ross-Hellauer, Tony and Sattler, Susanne and Thacker, Paul D. and Vanholsbeeck, Marc},
year = {2019},
keywords = {copyright, impact factor, open access, open science, peer review, research evaluation, scholarly communication, Scopus, web of science},
pages = {34}
}
@article{marwick_packaging_2018,
title = {Packaging {Data} {Analytical} {Work} {Reproducibly} {Using} {R} (and {Friends})},
volume = {72},
issn = {0003-1305},
doi = {10.1080/00031305.2017.1375986},
abstract = {Computers are a central tool in the research process, enabling complex and large-scale data analysis. As computer-based research has increased in complexity, so have the challenges of ensuring that this research is reproducible. To address this challenge, we review the concept of the research compendium as a solution for providing a standard and easily recognizable way for organizing the digital materials of a research project to enable other researchers to inspect, reproduce, and extend the research. We investigate how the structure and tooling of software packages of the R programming language are being used to produce research compendia in a variety of disciplines. We also describe how software engineering tools and services are being used by researchers to streamline working with research compendia. Using real-world examples, we show how researchers can improve the reproducibility of their work using research compendia based on R packages and related tools.},
number = {1},
journal = {The American Statistician},
author = {Marwick, Ben and Boettiger, Carl and Mullen, Lincoln},
year = {2018},
keywords = {Computational science, Data science, Open source software, Reproducible research},
pages = {80--88}
}
@article{pebesma_r_2012,
title = {The {R} software environment in reproducible geoscientific research},