Measured product lead custody receipt.
github.com/Zer0pa/ZPE-TasteRESEARCH-READY
LIVE
NEGATIVE RESULT
Failing at the geometry of taste.
Published null result on a taste-encoding object · ZPE-Taste · PyPI zpe-taste 0.1.0 · github.com/Zer0pa/ZPE-Taste
A taste object was tested as a geometry-bearing signal. It failed.
metric_fit scored 0.207 against a 0.6 threshold, and the three remaining geometry gates also missed. Identity controls returned 1.000, so the evaluator was working. The committed record holds four numbers, four thresholds, and the read-only commands that reproduce them. The geometry of taste has not been found; the next attempt no longer starts from zero.
01 · THE GAPNO PUBLISHED FLOOR
Taste geometry needs public negative results, not private dead ends.
02 · MARKETSRESEARCH CONTEXT
Sensory-encoding research and replication infrastructure — the budgets that fund taste work and the desks that read negative results.
03 · VALUE
$0.75B/yr
NIH BRAIN Initiative funds taste research; what they cannot fund is a vague private failure.
04 · INSIGHT
Taste was measured. The geometry wasn't there. the record is.
05.1 · CURRENT TECHPRIVATE NEGATIVE RESULTS
When a lab's taste-encoding model misses threshold, the numbers usually disappear into a private folder or a soft appendix. The next team rediscovers the same wall, with no way to know they have.
05.2 · OUR TECHTHE FLOOR PUBLISHED
ZPE-Taste commits the first openly-evaluated taste-geometry object as a record: 0.207 metric_fit, 0.156 topology_fit, 0.250 local injectivity, 0.181 graph_fit, all below their declared thresholds, with identity controls at 1.000 so the evaluator's verdict cannot be brushed off. Future taste-encoding work inherits a floor it has to clear.
05.3 · BENCHMARKSGEOMETRY EVALUATION
metric_fit0.207LOW
topology_fit0.156LOW
injectivity0.250LOW
graph_fit0.181LOW
Result: Four geometry metrics below threshold; identity controls at 1.000 — the evaluator was right to fail it.
06 · MEASUREMENTGEOMETRY RESULT LEDGER
Four geometry metrics measured. four missed the threshold.
06.1 · COMPARATIVE PERFORMANCE · GEOMETRY RESULT STATUS
From proofs/artifacts/taste_negative_reference.json: metric_fit 0.207 (gate 0.6), topology_fit 0.156 (gate 0.5), local_injectivity 0.250 (gate 0.5), graph_fit 0.181 (gate 0.5). Identity controls 1.000 across all four. Read-only checks: 4/4 PASS.
07 · KEY METRICSZPE-TASTE NEGATIVE REFERENCE
07.1 · METRIC FIT
0.207
Below 0.6 gate · metric_fit
07.2 · TOPOLOGY FIT
0.156
Below 0.5 gate · topology_fit
07.3 · LOCAL INJECTIVITY
0.250
Below 0.5 gate · local_injectivity
07.4 · GRAPH FIT
0.181
Below 0.5 gate · graph_fit
07.5 · RELEASE
0.1.0
PyPI zpe-taste · 0.1.1 pending
08 · REPRODUCIBILITYNEGATIVE RESULT
The negative result reproduces; the record is usable.
08.1 · WHAT REPLAYS EXACTLYFROZEN NEGATIVE PACKET
Determinism here means the negative packet is frozen: scores, thresholds, identity controls, and the read-only commands that confirm them. Clone the repo on any Python 3.8+ host and the same four below-threshold numbers come back, with the same evaluator behaviour.
What replays is not a taste reconstruction — it is the evidence that this geometry was tested, missed by these margins, and not silently retried. The next team can argue with the object or the metrics, but not with whether the experiment happened.
08.2 · HONEST BLOCKER
Honest Blocker ·
No positive taste codec exists. All four geometry metrics sit below threshold. Replay parity does not outrank a working decoder. The strongest evaluator control depends on full-packet identity. No external comparators have been published in this domain. PyPI zpe-taste 0.1.0 is stale; 0.1.1 is pending.
09
A published null unlocks the next question.
09.1 · THIS LAB'S AMBITION
The aim is not a taste encoder. It is a piece of scientific infrastructure: the first openly-evaluated taste-geometry object, committed as a negative with four scored metrics, declared thresholds, and identity controls. A taste-research field that argues over receptor-space versus psychophysical-space now has a number to argue against.
09.2 · WHAT THIS IS
A taste-geometry attempt scored, missed every gate, and shipped the numbers anyone can rerun.
09.3 · WHAT'S STILL OPEN
Which taste object should be encoded next: receptor-space, psychophysical-space, or something unnamed.
09.4 · REPLICATION · NEAR-TERM (12–24 MO)
Other labs start from a real floor
A second taste-encoding team can clone the record, run the same four metrics on their own candidate object, and report a number that means the same thing. The conversation about taste-geometry stops being anecdotal and starts being comparable.
09.5 · PROCUREMENT · NEAR-TERM (12–24 MO)
Program officers see what taste does not do
DARPA, ARO, and academic funders evaluating sensory-encoding proposals get a citable boundary they can hand to applicants: this is what failed, this is where the threshold sits, propose against it. Calibration replaces narrative.
09.6 · RETHINK · MID-TERM (24–48 MO)
The next taste model must clear a number
A research lead deciding between a receptor-space and a psychophysical-space encoder no longer chooses on intuition. Either approach has to beat 0.207 metric_fit and the three other gates, in public, before claiming the geometry of taste was found.
09.7 · SENSOR INDUSTRY · MID-TERM (24–48 MO)
E-tongue and taste-masking buyers ask harder questions
Beverage formulation chemists and pharma taste-masking analysts evaluating electronic-tongue platforms get a public-domain reference for what a published taste-geometry claim should look like. Vendor demos start needing the same four metrics, scored.
09.8 · OPEN SCIENCE · PARADIGM (48 MO+)
Sensory claims arrive with falsifiable scores
A field where any sensory-encoding paper — taste, smell, touch, interoception — is expected to ship measured geometry scores, declared thresholds, and identity controls. The cost of an unverified sensory claim rises; the value of a published null finally matches the value of a published positive.