{"id":"W4411227289","doi":"10.5463/thesis.1161","title":"Recognizing and interviewing suspects with intellectual disability","year":2025,"lang":"en","type":"dissertation","venue":"","topic":"Deception detection and forensic psychology","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Interview; Intellectual disability; Psychology; Data science; Computer science; Political science; Psychiatry; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01239022,0.0004047453,0.0006324439,0.003586604,0.004108296,0.003502793,0.001522503,0.001777141,0.001977208],"category_scores_gemma":[0.03623514,0.0006752213,0.0004004166,0.001575997,0.003225621,0.003577657,0.005184474,0.001764167,0.001136526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002526954,"about_ca_system_score_gemma":0.00671164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01152112,"about_ca_topic_score_gemma":0.02450118,"domain_scores_codex":[0.9890338,0.007738544,0.001021985,0.000474723,0.001141938,0.0005891122],"domain_scores_gemma":[0.9851342,0.008793767,0.002769098,0.0005483421,0.001898864,0.0008557553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006842247,0.00008282215,0.04416459,0.000993825,0.00001903023,0.005715235,0.8695563,0.0001594291,0.004576383,0.002223948,0.004920378,0.06751953],"study_design_scores_gemma":[0.0000102478,0.000163227,0.01693027,0.001612098,0.00002142442,0.00476929,0.9234383,0.000439557,0.001246955,0.003160885,0.04816528,0.0000425361],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9457654,0.006365689,0.01564535,0.01125644,0.00025182,0.001438457,0.0004049928,0.00007153943,0.01880033],"genre_scores_gemma":[0.9397375,0.01607989,0.03461037,0.00160353,0.0001432329,0.001006271,0.0004962185,0.00003295713,0.006289889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01239022,"threshold_uncertainty_score":0.06552649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04141673442488871,"score_gpt":0.3498670205008252,"score_spread":0.3084502860759366,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}