{"id":"W2549626564","doi":"10.1080/00450618.2016.1229816","title":"Expressing the value of forensic science in policing","year":2016,"lang":"en","type":"article","venue":"Australian Journal of Forensic Sciences","topic":"Wildlife Conservation and Criminology Analyses","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; International Centre for Comparative Criminology","funders":"","keywords":"Scrutiny; Scope (computer science); Criminal justice; Value (mathematics); Economic Justice; Object (grammar); Engineering ethics; Criminal investigation; Forensic science; Political science; Sociology; Epistemology; Criminology; Data science; Psychology; Computer science; Law; Engineering; Geography; Artificial intelligence","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":[0.1103248,0.001185051,0.00150929,0.006199467,0.01536002,0.04077991,0.004765841,0.02063599,0.002722996],"category_scores_gemma":[0.09404144,0.001168818,0.0009927966,0.003646411,0.132378,0.03927278,0.02212652,0.01502241,0.0009502147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01800858,"about_ca_system_score_gemma":0.01689622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005450988,"about_ca_topic_score_gemma":0.007081757,"domain_scores_codex":[0.8902854,0.08318727,0.00391486,0.003075617,0.01643583,0.003101096],"domain_scores_gemma":[0.8878766,0.0875793,0.005554827,0.00795586,0.009167585,0.001865775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000215207,0.0000135557,0.000362503,0.0001689299,0.0000204339,0.0002090196,0.02359062,0.0005393408,0.0001706669,0.9533444,0.003696889,0.01786222],"study_design_scores_gemma":[0.000006375422,0.00002169191,0.0002208363,0.0008052036,0.00001763647,0.0001587598,0.0118,0.0005113273,0.0002600024,0.9320511,0.05411085,0.00003622219],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02459039,0.03980613,0.09765431,0.5809973,0.004457737,0.0001486121,0.00007070402,0.0001106987,0.2521641],"genre_scores_gemma":[0.8842735,0.01665141,0.04079883,0.03984929,0.004733723,0.0001901724,0.00004606809,0.000123819,0.01333329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1103248,"threshold_uncertainty_score":0.5834605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07060996152713937,"score_gpt":0.3216149938463252,"score_spread":0.2510050323191858,"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."}}