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Record W2124010887 · doi:10.1080/02699050400005242

The Rey 15-item memory test for malingering: A meta-analysis

2004· review· en· W2124010887 on OpenAlex

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

VenueBrain Injury · 2004
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreUniversity of Toronto
Fundersnot available
KeywordsMalingeringTest (biology)False positive paradoxMemory testPsychologyMeta-analysisClinical psychologyPsychiatryMedicineArtificial intelligenceComputer scienceCognitionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Rey 15-Item Memory Test (RMT) is frequently used to detect malingering. Many objections to the test have been raised. Nevertheless, the test is still widely used. OBJECTIVE: To provide a meta-analysis of the available studies using the RMT and provide an overall assessment of the sensitivity and specificity of the test, based on the cumulative data. RESULTS: The results show that, excluding patients with mental retardation, the RMT has a low sensitivity but an excellent specificity. CONCLUSIONS: These results provide the basis for the ongoing use of the test, given that it is acceptable to miss some cases of malingering with such a screening test, but one does not want to have many false positives.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.061
GPT teacher head0.334
Teacher spread0.273 · 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