{"id":"W1844718490","doi":"10.1002/acp.2898","title":"Facilitating Accuracy in Showup Identification Procedures: The Effects of the Presence of Stolen Property","year":2012,"lang":"en","type":"article","venue":"Applied Cognitive Psychology","topic":"Memory Processes and Influences","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; Queen's University","funders":"","keywords":"Property (philosophy); Identification (biology); Context (archaeology); Psychology; Law enforcement; Logistic regression; Enforcement; Sensitivity (control systems); Social psychology; Computer security; Law; Computer science; Machine learning; Engineering; Political science; History","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":[0.003761321,0.0003271595,0.0002899302,0.0003947901,0.0004736822,0.001179718,0.0004092111,0.0005454534,0.002076011],"category_scores_gemma":[0.07438317,0.0003783685,0.0002616297,0.0001721666,0.0007802953,0.001123678,0.001296006,0.000934487,0.0004037741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002850064,"about_ca_system_score_gemma":0.0003036275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00161592,"about_ca_topic_score_gemma":0.002236989,"domain_scores_codex":[0.9968109,0.001616078,0.0003071266,0.0003109428,0.0007356119,0.0002192796],"domain_scores_gemma":[0.9308733,0.04863386,0.01199198,0.004501735,0.002242531,0.001756512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.007213438,0.001592702,0.8404681,0.0001678763,0.0002583136,0.000584619,0.006933243,0.001423125,0.0589397,0.0002461111,0.0003894038,0.08178319],"study_design_scores_gemma":[0.00002646782,0.001828117,0.9797801,0.00004351866,0.00009109398,0.0004960278,0.001676667,0.001892118,0.01348739,0.0003071614,0.0003382267,0.00003310589],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994211,0.0000386928,0.0001634074,0.00002343786,0.000003376844,0.000004903476,0.000006552634,0.000006041113,0.0003324659],"genre_scores_gemma":[0.9994934,0.0000408944,0.0002974857,0.00001479593,0.000004847481,0.000004035882,0.00001779112,0.000004958514,0.0001217139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003761321,"threshold_uncertainty_score":0.01989198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04323049973143665,"score_gpt":0.3427632556081706,"score_spread":0.2995327558767339,"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."}}