{"id":"W2160364387","doi":"10.1177/0093854808321879","title":"Logic and Research Versus Intuition and Past Practice as Guides to Gathering and Evaluating Eyewitness Evidence","year":2008,"lang":"en","type":"article","venue":"Criminal Justice and Behavior","topic":"Memory Processes and Influences","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Intuition; Psychology; Legal psychology; Law enforcement; Eyewitness identification; Perspective (graphical); Eyewitness testimony; Empirical evidence; Enforcement; Social psychology; Cognition; Criminology; Law; Political science; Epistemology; Cognitive science; Computer science; Relation (database)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1978289,0.001568815,0.001554832,0.01518692,0.004776321,0.02447527,0.005608927,0.007350999,0.004194332],"category_scores_gemma":[0.3164021,0.00112691,0.001112011,0.005956008,0.1051108,0.02377458,0.009933299,0.01123852,0.00145009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01168936,"about_ca_system_score_gemma":0.01621875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004433391,"about_ca_topic_score_gemma":0.005794409,"domain_scores_codex":[0.7754422,0.1897938,0.01312803,0.00619751,0.01315026,0.002288291],"domain_scores_gemma":[0.5370629,0.3846382,0.02140702,0.02697007,0.02444621,0.005475662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001151731,0.0001178166,0.002370283,0.001363399,0.00005569421,0.0003298702,0.05969718,0.0006438091,0.0004703084,0.8532417,0.01265714,0.06893767],"study_design_scores_gemma":[0.0001225091,0.0001406472,0.001206521,0.002885834,0.00004483516,0.0004061125,0.03723354,0.002574657,0.001405806,0.8501967,0.1036662,0.0001166437],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04458097,0.02376553,0.5122306,0.2265046,0.003439916,0.003331922,0.0002601274,0.001566051,0.1843202],"genre_scores_gemma":[0.4129539,0.007891916,0.5449877,0.0210215,0.0007087628,0.003439132,0.0001056754,0.0004097144,0.008481631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1978289,"threshold_uncertainty_score":0.9892198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5643495498846955,"score_gpt":0.5289948928824291,"score_spread":0.03535465700226648,"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."}}