Datasets:
Using the FSOT Physical Archive for PFLT
Master: I:\FSOT-Physical-Archive\02_FSOT-2.1-Lean-Full (I: definitive; GitHub is sync-from-I)
Always
Law: vendor/fsot_compute.py pin D1D38A
Scalar: S = K*(T1+T2+T3) from seeds only
Domain: linguistic D_eff=12, observed=true for converse
Students: densify/morph/phrase — never rewrite law
Grab for translation fluency
| Archive path | Use |
|---|---|
vendor/fsot_compute.py |
Authority pin + compute_scalar |
vendor/linguistics/linguistics_derivations.json |
Zipf, dep length, sentence length |
vendor/linguistics/data/LINGUISTIC_TARGETS.csv |
Empirical gates |
data/linguistics_formal_benchmark.json |
D_eff=12 panel culture |
FSOT/Scalar.lean |
Formal T1/T2/T3 structure |
docs/PRACTICAL_PIPELINE.md |
Offline validation → application |
Commands
cd pflt-Ada
python fsot_archive_fluency_push.py
python fsot_solve_fluency_gap.py