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Record W3037540123 · doi:10.1177/0956797619885607

Weak and Variable Effects of Exogenous Testosterone on Cognitive Reflection Test Performance in Three Experiments: Commentary on Nave, Nadler, Zava, and Camerer (2017)

2020· letter· en· W3037540123 on OpenAlexafffund
Erik L. Knight, Blakeley B. McShane, Hana H. Kutlikova, Pablo J. Morales, Colton B. Christian, William T. Harbaugh, Ulrich Mayr, Triana L. Ortiz, Kimberly Gilbert, Christine Ma‐Kellams, I Riečanský, Neil V. Watson, Christoph Eisenegger, Claus Lamm, Pranjal H. Mehta, Justin M. Carré

Bibliographic record

VenuePsychological Science · 2020
Typeletter
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsSimon Fraser UniversityNipissing UniversityKellogg's (Canada)
FundersDivision of Behavioral and Cognitive SciencesNatural Sciences and Engineering Research Council of CanadaDivision of Social and Economic SciencesNational Institute on AgingVienna Science and Technology FundNorthern Ontario Heritage Fund Corporation
KeywordsNavePsychologyTest (biology)Reflection (computer programming)Variable (mathematics)CognitionCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.031
metaresearch head score (Gemma)0.141
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.072
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.141
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.002
Science and technology studies0.0050.007
Scholarly communication0.0040.004
Open science0.0060.003
Research integrity0.0720.069
Insufficient payload (model declined to judge)0.0060.007

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 head0.095
GPT teacher head0.410
Teacher spread0.314 · 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
GenreCommentary

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

Citations15
Published2020
Admission routes2
Has abstractno

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