{"id":"W3124791754","doi":"10.22215/etd/2016-11648","title":"Improving Eyewitness Identification Accuracy with a Modified Lineup Procedure","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Deception detection and forensic psychology","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Witness; Eyewitness identification; Psychology; Identification (biology); Confidence interval; Social psychology; Statistics; Computer science; Data mining; Mathematics","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":[0.001338036,0.0004930045,0.0004253413,0.000339789,0.0001558717,0.0004502699,0.0005626488,0.0005290966,0.002730931],"category_scores_gemma":[0.01026561,0.0001916834,0.0002213571,0.00017259,0.0002487843,0.001008392,0.0004791789,0.0007027421,0.0006364335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001628469,"about_ca_system_score_gemma":0.0002339149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002758795,"about_ca_topic_score_gemma":0.0004962575,"domain_scores_codex":[0.9991998,0.0002029644,0.0001095137,0.0001500663,0.0002740015,0.00006379181],"domain_scores_gemma":[0.9928174,0.003618457,0.001739303,0.001134296,0.0004941082,0.0001964414],"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":[0.0103834,0.007836277,0.02147708,0.0005816366,0.0001383564,0.0004888047,0.001250179,0.00123246,0.6019845,0.0006538761,0.0009836248,0.3529899],"study_design_scores_gemma":[0.001148189,0.06818845,0.3071631,0.0001835159,0.0005092697,0.006148729,0.0008429799,0.021908,0.5842152,0.001473618,0.007938758,0.0002802914],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926268,0.0000925612,0.006157346,0.00005754703,0.00002173749,0.000125742,0.00003732912,0.0002154803,0.0006653829],"genre_scores_gemma":[0.975065,0.0001606381,0.0228031,0.0001494575,0.00002942881,0.0001668006,0.0001220684,0.00005396695,0.001449574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002730931,"threshold_uncertainty_score":0.009135902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01911667580254595,"score_gpt":0.3353453047463226,"score_spread":0.3162286289437766,"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."}}