{"id":"W3017253864","doi":"10.1080/00085030.2020.1748284","title":"Comparing jury focus and comprehension of expert evidence between adversarial and court-appointed models in Canadian criminal court context","year":2020,"lang":"en","type":"article","venue":"Canadian Society of Forensic Science Journal","topic":"Jury Decision Making Processes","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"","keywords":"Adversarial system; Jury; Context (archaeology); Criminal case; Criminal court; Law; Focus (optics); Comprehension; Criminology; Psychology; Jury instructions; Political science; Computer science; History; International law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.01210607,0.0004391937,0.0005105422,0.00299164,0.01097934,0.007210754,0.002281092,0.001624958,0.01016589],"category_scores_gemma":[0.08015382,0.0004846324,0.0004899848,0.001915156,0.005370612,0.002685028,0.004239926,0.001863826,0.0004431898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06459653,"about_ca_system_score_gemma":0.05248069,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9082973,"about_ca_topic_score_gemma":0.9413267,"domain_scores_codex":[0.9895284,0.003549703,0.0004812589,0.0009491701,0.003730582,0.001760854],"domain_scores_gemma":[0.975977,0.01106847,0.003277134,0.000799123,0.005522503,0.003355903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.001345217,0.0007018294,0.2602279,0.0004978852,0.0001542356,0.001730303,0.6056998,0.001795188,0.00292653,0.03082344,0.01175959,0.08233814],"study_design_scores_gemma":[0.0001851332,0.0004249213,0.6241034,0.0008466771,0.0001728654,0.0003471907,0.3276596,0.004073204,0.0009177692,0.01019245,0.03064403,0.0004328635],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688306,0.0004788282,0.0005035315,0.002371164,0.00003650413,0.0001359497,0.0001280794,0.00001927392,0.02749608],"genre_scores_gemma":[0.9975082,0.0002287826,0.0003269312,0.0002151693,0.000008541601,0.00003290558,0.00005930512,0.000007604328,0.001612527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0917027,"threshold_uncertainty_score":0.4686828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1354321480218602,"score_gpt":0.3449763169649397,"score_spread":0.2095441689430795,"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."}}