pflt-fsot-sample / docs /ADA_ARCHIVE_SENSORY.md
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Ada ↔ FSOT Physical Archive + sensory + gap-fill (V6)

Archive master: I:\FSOT-Physical-Archive
Product binary: pflt-Ada/bin/pflt_main.exe (Ada-primary V6)


Gaps filled (this pass)

Gap Implementation CLI
1. Full domain atlas (~400) domain_atlas.tsv (410 rows from catalog) + PFLT_Atlas keyword match → D_eff panel atlas "quantum photon"
2. Live SHA256 pin Pure Ada PFLT_SHA256 hashes archive fsot_compute.py vs D1D38A… archivelive_hash_ok=TRUE
3. U-Net hypothesis slot Load TSV hyp file → Gardiner teacher (store/Unikemet); image path metadata vision unet / vision hyp PATH [image]
4. SR-ITE LTM / mulling Append-only ltm_mulling.jsonl; recall + densify mull notes ltm recall KEY · auto on converse
5. Certified math Law panel + refuse vibes S= cert "fsot scalar"
6. Linguistics anchors 60 archive derivations in TSV; zipf/entropy/… cert "zipf entropy" · wired into converse

Archive binding (verified live)

live_hash_ok=TRUE
live_sha256=D1D38A185487B452E470AC68ECE2EB45AEB1CA9CE25FC9BF9564C19633FFBE70
expected_sha256=D1D38A185487B452E470AC68ECE2EB45AEB1CA9CE25FC9BF9564C19633FFBE70
note=LIVE pin OK: archive fsot_compute.py SHA256 = D1D38A

Formula still S=K*(T1+T2+T3); golden linguistic S≈0.651324761885.


Data export

cd C:\Users\damia\Desktop\pflt\pflt-Ada
python export_atlas_for_ada.py   # domain_atlas + anchors + unet sample hyp
python export_data_for_ada.py    # densify/gold/train_mass
alr build

CLI map

.\bin\pflt_main.exe archive
.\bin\pflt_main.exe atlas "astronomy quantum linguistics"
.\bin\pflt_main.exe cert "what is zipf entropy and fsot scalar"
.\bin\pflt_main.exe vision unet
.\bin\pflt_main.exe vision A1 N5 S34
.\bin\pflt_main.exe audio aqua la
.\bin\pflt_main.exe converse "what is zipf and aqua lingua"
.\bin\pflt_main.exe ltm recall aqua
.\bin\pflt_main.exe status
.\bin\pflt_main.exe eval

Architecture (students vs law)

I:\FSOT-Physical-Archive  (constitution)
   vendor/fsot_compute.py  --LIVE SHA256 D1D38A-->  Ada kernel pin
   linguistics_derivations --> anchors.tsv --> cert gate
   domain catalog 402      --> domain_atlas.tsv --> atlas route

Sensory students (never rewrite law):
   vision: multilayer field | Gardiner labels | U-Net hyp TSV
   audio:  IPA + articulatory + S→tempo/energy
   morph:  reverse peels + train_mass

Product surface:
   converse = translate + atlas + pathway + teach + cert + LTM + ledger

Still later (honest residual)

  • Real raster image decode + trained U-Net weights (hyp TSV contract is ready)
  • Full Lean bridge process spawn on every numeric claim (Ada cert uses golden panel + anchors)
  • SR-ITE continuous stream driver (Zig/photonic) — LTM file is the portable subset
  • 402 domains fully drive pathway enum (today: atlas string match + core Domain_Id enum)

One-line

V6 closes the archive/sensory/cert gaps: live D1D38A, 410-domain atlas, anchors+cert, U-Net hyp load, LTM mulling — all under Ada product binary.