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Record W4243171438 · doi:10.31234/osf.io/9hc8n

Response-locked component of error monitoring in psychopathy: A systematic review and meta-analysis of error-related negativity/positivity

2020· review· en· W4243171438 on OpenAlexaff
William Vallet, Cécilia Neige, Sabine MOUCHET-MAGES, Jérôme Brunelin, Simon Grondin

Bibliographic record

Venuenot available
Typereview
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPsychopathyPsychologyConstruct (python library)ConceptualizationDevelopmental psychologyAntisocial personality disorderInterpersonal communicationCognitive psychologyPersonalityPoison controlSocial psychologyInjury preventionMedicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Prior findings reported that externalizing behaviors are closely related to disturbances in error monitoring. It has been suggested that these impairments are not applied to individuals with psychopathy. However, mixed results are reported in the field considering the etiological heterogeneity of the psychopathy construct. Most of the scales for the assessment of psychopathic traits use a modern conception of psychopathy. This conception suggests a pathological personality construct comprising factor conceptualization rather than a unitary construct. Deficits in error-related processing measures with event-related potential components are reported among individuals with psychopathy, but it is unclear whether these deficits are modulated by an interpersonal-affective or an impulsive-antisocial dimension

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)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.189
GPT teacher head0.431
Teacher spread0.242 · 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 designMeta-analysis
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

Citations0
Published2020
Admission routes1
Has abstractyes

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