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Record W2752101833 · doi:10.3389/fpsyg.2017.01457

Corrigendum: Psychopaths Show Enhanced Amygdala Activation during Fear Conditioning

2017· erratum· en· W2752101833 on OpenAlexaboutno aff
Douglas H. Schultz

Bibliographic record

VenueFrontiers in Psychology · 2017
Typeerratum
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAmygdalaFear conditioningNeuroscienceCognitive psychology

Abstract

fetched live from OpenAlex

There was a mistake in one of the papers referenced as published. Originally we cited: Hare,R.D., and Vertommen, H. (2003). The Hare Psychopathy Checklist-Revised. Toronto, ON: Multi-Health Systems. This citation is inaccurate. The reference should appear as: Hare, R. D. (2003). The Hare Psychopathy Checklist-Revised, 2nd edition. Toronto, ON: Multi-Health SystemsAdditionally, the paper is cited in the text multiple times on page 2. The in-text citations should appear as (Hare, 2003).The authors apologize for the mistake. This error does not change the scientific conclusions of the article in any way.

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)0.003
metaresearch head score (Gemma)0.037
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 score0.115
Threshold uncertainty score0.386

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.037
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.1150.052

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 head0.032
GPT teacher head0.325
Teacher spread0.293 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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