Now the junior analyst meets the answer key. You build extract/agent.py with two brains, a frontier model through the API and a local Qwen on your 3050, plus a fake brain for tests. Then you do the thing that distinguishes an AI scientist from an AI enthusiast: you measure it per field, not as one flattering average. It will be very good at "organism" and bad at "working volume", and that unevenness is the finding. …
If you only do one thing this week: the F1 table, whatever it says
Saturday sandbox
· after 3Blue1Brown "Bayes theorem, the geometry of changing beliefs"
STRENDA guidelines (Standards for Reporting Enzymology Data) — search "STRENDA guidelines" (verify URL). A real "minimum information" standard; it shows what a reporting checklist looks like and will inspire your completeness analysis
By Sunday you should be able to say: “I can read my own F1 table aloud, say why the worst field fails, and explain why tuning on the gold set is dangerous.”