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Record W2092649829 · doi:10.1093/schbul/sbm056

On the Centrality and Significance of Stimulus-Encoding Deficit in Schizophrenia

2007· review· en· W2092649829 on OpenAlexafffund
Richard W. J. Neufeld

Bibliographic record

VenueSchizophrenia Bulletin · 2007
Typereview
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsCognitionCognitive deficitCognitive psychologyPsychologyStimulus (psychology)InferenceEncoding (memory)Cognitive scienceNeuroscienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Increased latency of stimulus encoding is presented as a central deficit in schizophrenia cognition. Encoding, here, entails the internal representation of presenting stimuli in a format facilitating their implementation in other cognitive processes, such as those taking place in working memory. Historical roots of suspected encoding debility in schizophrenia briefly are reviewed, and its singular empirical robustness is described. More recently, this deficit has been subjected to stochastic mathematical modeling, resulting in its decomposition into discrete cognitive functions. A nonmathematical exposition of this account is provided, and substantial behavioral study support is illustrated. Implications for clinical assessment of individuals and of treatment regimens, with respect to encoding-related cognitive efficiency, are noted. Finally, because stochastic dynamic trajectories of process duration are modeled, times of measurement interest, complementing neuroanatomical regions of interest, become available for enhanced temporal navigation of event-related fMRI. Results from recent implementations of such process-defined events are described.

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 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)0.002
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.079
GPT teacher head0.313
Teacher spread0.234 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2007
Admission routes2
Has abstractyes

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