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Record W3186858856 · doi:10.1037/bne0000461

Orbitofrontal cortex and learning predictions of state transitions.

2021· article· en· W3186858856 on OpenAlex
Stephanie C. Y. Chan, Nicolas W. Schuck, Nina Lopatina, Geoffrey Schoenbaum, Yael Niv

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehavioral Neuroscience · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsL'Alliance Boviteq
FundersArmy Research LaboratoryArmy Research OfficeNational Institute on Drug AbuseNational Institute of Mental HealthNational Institutes of HealthMax-Planck-GesellschaftEuropean Commission
KeywordsOrbitofrontal cortexPsychologyPsycINFOOutcome (game theory)Brain activity and meditationCognitive psychologyProbabilistic logicNeurosciencePrefrontal cortexArtificial intelligenceCognitionComputer scienceChemistryElectroencephalographyMEDLINE

Abstract

fetched live from OpenAlex

cue that was observed at the time of OFC activity-this relationship was not observed for subsequent trials involving a different cue. All together, these results indicate that the OFC is involved in updating or reinforcing a learned transition model on a trial-by-trial basis, specifically for the currently observed cue-outcome associations. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.122
GPT teacher head0.367
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it