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One should check for keywords explicitly indicating non-relevance for HEP and display the numbers.
Expected Behavior
bibclassify should run on the abstract+title+author keywords with the antiHEP-ontology (see #2282). The number of anti-CORE-keywords should be displayed. I have no experience with running it on the fulltext but I would expect too many false positives.
These numbers should also be handed over to the function calculating the automatic decision whether to take or reject a record.
Current Behavior
None in the actual holdingpen. In the DESY-workflow, we do it.
Context
For many instrumental or other papers rather at the surrounding research fields finding no core keywords does not necessarily mean that the paper is not interesting for us. But if the abstract contains "biological", "cardiac" and "in vivo" it's clear that we can reject it.
The text was updated successfully, but these errors were encountered:
One should check for keywords explicitly indicating non-relevance for HEP and display the numbers.
Expected Behavior
bibclassify should run on the abstract+title+author keywords with the antiHEP-ontology (see #2282). The number of anti-CORE-keywords should be displayed. I have no experience with running it on the fulltext but I would expect too many false positives.
These numbers should also be handed over to the function calculating the automatic decision whether to take or reject a record.
Current Behavior
None in the actual holdingpen. In the DESY-workflow, we do it.
Context
For many instrumental or other papers rather at the surrounding research fields finding no core keywords does not necessarily mean that the paper is not interesting for us. But if the abstract contains "biological", "cardiac" and "in vivo" it's clear that we can reject it.
The text was updated successfully, but these errors were encountered: