{"id":"W2018493280","doi":"10.1177/1098611109339892","title":"Creating Blind Photoarrays Using Virtual Human Technology","year":2009,"lang":"en","type":"article","venue":"Police Quarterly","topic":"Deception detection and forensic psychology","field":"Psychology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Officer; Suspect; Identification (biology); Field (mathematics); Resource (disambiguation); Psychology; Identity (music); Applied psychology; Computer science; Political science","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":[0.002105249,0.0005776332,0.0003668507,0.0006701614,0.000881809,0.001689639,0.0008774239,0.0007045426,0.007340165],"category_scores_gemma":[0.009248737,0.000335657,0.0003672233,0.0002013441,0.001517923,0.002628242,0.003200027,0.0005728217,0.001196327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002489727,"about_ca_system_score_gemma":0.0006106758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003002967,"about_ca_topic_score_gemma":0.0003902958,"domain_scores_codex":[0.9981865,0.0009809543,0.00007291947,0.0002767042,0.0003150096,0.0001678371],"domain_scores_gemma":[0.9943023,0.003194856,0.0004657923,0.001274418,0.0003543561,0.0004082443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003876491,0.004146037,0.01632451,0.001049921,0.0001071409,0.00174596,0.02493563,0.007688295,0.2382632,0.02718963,0.008048705,0.6666245],"study_design_scores_gemma":[0.001182205,0.02263865,0.0395051,0.0007364759,0.0004105663,0.008751954,0.02188169,0.05802993,0.5515311,0.02721973,0.2674783,0.0006341957],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7627478,0.0004251868,0.2146994,0.0005183309,0.0002569105,0.000831036,0.00007297991,0.001744425,0.01870397],"genre_scores_gemma":[0.8451907,0.0002825355,0.1456383,0.000281832,0.00005234043,0.0003773882,0.00006746587,0.0001415541,0.007967886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007340165,"threshold_uncertainty_score":0.02455527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.038059196981713,"score_gpt":0.3726637848739618,"score_spread":0.3346045878922488,"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."}}