BioForge v6.2.2 — Mapping accuracy validated (99.8% on real E. coli)

Fast is worthless if it's wrong — so here's the proof it isn't. No engine
changes; a new benchmark tool + the result in the README.

── Install ──────────────────────────────────────────────────
pip install bioforge (Python >= 3.10, NumPy only)

Added

• tools/accuracy_vs_minimap2.py — measures mapping ACCURACY on a real genome:
  simulates reads recording each read's true origin, maps with BioForge and
  minimap2, and counts how many land at the correct position (±tolerance). Real
  genomes have repeats — the hard case.

Result (E. coli K-12, 4.64 Mb, 5000 reads, ±50 bp)

• 5% error: BioForge 99.8% correct · minimap2 99.8% · 99.8% concordance
• 10% error: BioForge 99.7% · minimap2 99.9%
• As accurate as minimap2 — not fast-at-the-cost-of-correctness. Honest note: at
  higher error minimap2 is marginally ahead, and this is E. coli scale.