Specific and Reactive Sensitivities of Skin Resistance Response and Respiratory Apnea in a Japanese Concealed Information Test (CIT) of Criminal Guilt.
Bibliographic record
Abstract
La sensibilite reactive lors du test psychophysiologique appele Concealed Information Test (CIT) utilise pour induire la culpabilite criminelle se rapporte au degre selon lequel les reactions autonomes de lapersonne qui subit le test en reponse aux propositions rattachees aux details du crime que l'on sait etre connus seulement du coupable sont plus importantes que les reactions aux propositions dont on ne connait pas la veracite. Les mecanismes psychologiques hypothetiques qui interviennent dans la sensibilite reactive au CIT sont en regle generale consideres comme etant d'ordre attentionnel, d'orientation ou cognitif plutot que d'ordre emotionnel. Toutefois, le CIT comporte une composante emotionnelle potentielle, en particulier lorsque le test est administre sur le terrain plutot qu'en laboratoire. Cette composante emotionnelle depend des questions de comparaison qui sont etroitement reliees a un crime (grave et qui suppose par consequent un contenu plus emotif) par rapport aux questions qui sont moins reliees. Dans la presente etude (qui ne relate pas une experience faisant appel a la manipulation de variables independantes), les resultats obtenus sur le CIT par 30 suspects japonais ayant, par la suite, ete trouves coupables d'un crime grave sont examines sous l'angle de la mesure conventionnelle de la resistance de la peau et d'une nouvelle mesure, introduite recemment, de la reponse respiratoire et apneique (qui est rarement utilisee en laboratoire mais frequemment sur le terrain). Seule la mesure respiratoire a demontre la presence d'une sensibilite specifique significative; les deux mesures ont demontre une sensibilite reactive non differentielle et fortement significative.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".