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Record W2902765481 · doi:10.1002/acp.3504

Intoxicated eyewitnesses: The effect of a fully balanced placebo design on event memory and metacognitive control

2018· article· en· W2902765481 on OpenAlexaff
Julie Gawrylowicz, Alan Scoboria, Rachel D. Teodorini, Ian P. Albery

Bibliographic record

VenueApplied Cognitive Psychology · 2018
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Windsor
FundersBritish AcademyLeverhulme Trust
KeywordsPsychologyCued recallRecallPlaceboFree recallAlcoholMetacognitionDevelopmental psychologyCognitive psychologySocial psychologyCognitionPsychiatryMedicine

Abstract

fetched live from OpenAlex

Summary Few studies have examined the impact of alcohol on metacognition for witnessed events. We used a 2 × 2 balanced placebo design, where mock witnesses expected and drank alcohol, did not expect but drank alcohol, did not expect nor drank alcohol, or expected but did not drink alcohol. Participants watched a mock crime in a bar‐lab, followed by free recall and a cued‐recall test with or without the option to reply “don't know” (DK). Intoxicated mock witnesses' free recall was less complete but not less accurate. During cued‐recall, alcohol led to lower accuracy, and reverse placebo participants gave more erroneous and fewer correct responses. Permitting and clarifying DK responses was associated with fewer errors and more correct responses for sober individuals; and intoxicated witnesses were less likely to opt out of erroneous responding to unanswerable questions. Our findings highlight the practical and theoretical importance of examining pharmacological effects of alcohol and expectancies in real‐life settings.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.334
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations9
Published2018
Admission routes1
Has abstractyes

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