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Record W2155734565 · doi:10.1037/0021-9010.86.4.674

A quantitative review of the Guilty Knowledge Test.

2001· review· en· W2155734565 on OpenAlex
Vance V. MacLaren

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Psychology · 2001
Typereview
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPolygraphPsychologyLie detectionTest (biology)Social psychologyStatisticsApplied psychologyClinical psychologyDeception

Abstract

fetched live from OpenAlex

The guilty knowledge polygraph test (GKT; D. T. Lykken, 1959, 1960) is a psychophysiological method of identifying suspects with concealed information about a crime. A meta-analysis of 50 treatment groups drawn from 22 laboratory simulation studies (total N = 1,247) was conducted to provide a comprehensive estimate of GKT accuracy under controlled conditions. Electrodermal measures correctly identified 76% of participants with concealed knowledge and 83% of those without information. Informed participants were detected at rates significantly in excess of chance, with a mean weighted effect size of .57. Enactment of mock crimes increased the hit rate to 82%. The rates of false-positive error among noninformed treatment groups did not significantly exceed chance. Applications and research directions are discussed.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.665
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.136
GPT teacher head0.487
Teacher spread0.351 · 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