{"id":"W2015319625","doi":"10.1037/0021-9010.89.1.73","title":"Multiple Independent Identification Decisions: A Method of Calibrating Eyewitness Identifications.","year":2004,"lang":"en","type":"article","venue":"Journal of Applied Psychology","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Suspect; Psychology; Eyewitness identification; Witness; Identification (biology); Social psychology; Cognitive psychology; Data mining; Computer 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009361187,0.0001058717,0.0002452062,0.0003755633,0.0001023355,0.0000380153,0.000323268,0.0001305911,0.0001716637],"category_scores_gemma":[0.0006048277,0.00009567929,0.0001113234,0.0004346798,0.0000977721,0.0002166611,0.00002468684,0.0002882276,0.0000996473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004416735,"about_ca_system_score_gemma":0.0000649904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004011958,"about_ca_topic_score_gemma":0.000006031957,"domain_scores_codex":[0.9981102,0.0001395182,0.0009742607,0.0002553741,0.0003710767,0.0001495608],"domain_scores_gemma":[0.9981008,0.0004016536,0.000990715,0.0002557464,0.0001658371,0.00008527028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001594276,0.0002648887,0.0000618778,0.000007399784,0.00000801801,0.000004301104,0.0007187059,0.001538277,0.9624391,0.003389337,0.0001283483,0.03128032],"study_design_scores_gemma":[0.003499743,0.0001377907,0.01981229,0.00007678958,0.00004895486,0.0004709011,0.0008842913,0.0003240141,0.9204955,0.05294701,0.001098098,0.000204622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5929042,0.00001842252,0.4041006,0.000610579,0.0006323422,0.0001949717,0.00001083153,0.00001649045,0.001511552],"genre_scores_gemma":[0.9789206,0.0001303787,0.02026034,0.000550031,0.00008089078,0.00001335757,0.000003670134,0.00001407597,0.00002662949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3860164,"threshold_uncertainty_score":0.3901688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09203157892086189,"score_gpt":0.3995930806916237,"score_spread":0.3075615017707618,"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."}}