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Record W2166008604 · doi:10.1093/schbul/sbp039

Reinforcement Ambiguity and Novelty Do Not Account for Transitive Inference Deficits in Schizophrenia

2009· article· en· W2166008604 on OpenAlexaff
Michael J. Coleman, Debra Titone, Olga Krastoshevsky, Verena Krause, Zhuying Huang, Nancy R. Mendell, Howard Eichenbaum, Deborah L. Levy

Bibliographic record

VenueSchizophrenia Bulletin · 2009
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsMcGill University
FundersNational Institute of Mental Health
KeywordsNoveltySchizophrenia (object-oriented programming)PsychologyAmbiguityTask (project management)ReinforcementCognitive psychologyTransitive relationInferenceDevelopmental psychologyNeurosciencePsychiatryArtificial intelligenceComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

The capacity for transitive inference (TI), a form of relational memory organization, is impaired in schizophrenia patients. In order to disambiguate deficits in TI from the effects of ambiguous reinforcement history and novelty, 28 schizophrenia and 20 nonpsychiatric control subjects were tested on newly developed TI and non-TI tasks that were matched on these 2 variables. Schizophrenia patients performed significantly worse than controls on the TI task but were able to make equivalently difficult nontransitive judgments as well as controls. Neither novelty nor reinforcement ambiguity accounted for the selective deficit of the patients on the TI task. These findings implicate a disturbance in relational memory organization, likely subserved by hippocampal dysfunction, in the pathophysiology of schizophrenia.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.301
Teacher spread0.247 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2009
Admission routes1
Has abstractyes

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