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Record W4251386946 · doi:10.3389/fnint.2013.00048

Erratum: Noradrenergic control of error perseveration in medial prefrontal cortex

2013· erratum· en· W4251386946 on OpenAlexaff
Mark Laubach

Bibliographic record

VenueFrontiers in Integrative Neuroscience · 2013
Typeerratum
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of British Columbia
FundersEllison Medical FoundationNational Institute on AgingNational Science Foundation
KeywordsPerseverationPrefrontal cortexNeurosciencePsychologyCognitive psychologyCognition

Abstract

fetched live from OpenAlex

The paper should have listed support from the National Science Foundation (NSF). Two authors (Stachenfeld and Laubach) were supported with funds from NSF grant 1121147 to Mark Laubach. The correct acknowledgment is:“This work was supported by Public Health Service Grant PO1AG030004 from the National Institute on Aging (Amy F. T. Arnsten and Mark Laubach), the National Science Foundation 1121147 (Mark Laubach) and by AFAR/Ellison Medical Foundation Post-doctoral Fellowship (Marcelo S. Caetano).”

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)0.004
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0350.024

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 head0.065
GPT teacher head0.334
Teacher spread0.268 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2013
Admission routes1
Has abstractyes

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