{"id":"W4391457406","doi":"10.1504/ijfem.2023.136381","title":"Bridging forensic sciences and management: forensic assessment of technologies effectiveness pre-acquisition index for forensic sciences laboratories","year":2023,"lang":"en","type":"article","venue":"International Journal of Forensic Engineering and Management","topic":"Technology Assessment and Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Forensic science; Bridging (networking); Forensic psychology; Computer science; Psychology; Medicine; Computer security; Criminology","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":[0.006752914,0.0006770313,0.000573557,0.01375761,0.0009552285,0.004191091,0.000906735,0.0009516598,0.009397938],"category_scores_gemma":[0.02700633,0.0001949802,0.0003994792,0.006852456,0.001144088,0.003937338,0.002630479,0.0008992703,0.002225132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001986997,"about_ca_system_score_gemma":0.002758726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001100843,"about_ca_topic_score_gemma":0.001927985,"domain_scores_codex":[0.9926279,0.001220876,0.0008432267,0.0002815399,0.004728988,0.0002975083],"domain_scores_gemma":[0.9783408,0.007052983,0.00559537,0.001085298,0.006866354,0.001059297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004011603,0.0005694981,0.1619847,0.001763893,0.0001935786,0.0002192878,0.001979116,0.003958712,0.006344276,0.0305926,0.0652284,0.7267648],"study_design_scores_gemma":[0.00005107266,0.001177198,0.6384029,0.001478085,0.0002849762,0.001571167,0.008308096,0.02684145,0.02525105,0.04993269,0.2464212,0.0002801698],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.44639,0.006682032,0.1571541,0.00928514,0.0008189671,0.00226356,0.02336998,0.001712561,0.3523237],"genre_scores_gemma":[0.8510012,0.002808513,0.1203622,0.0003958066,0.000330172,0.001158834,0.007856417,0.0001294941,0.01595733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01375761,"threshold_uncertainty_score":0.0357132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00801988221821849,"score_gpt":0.2738447125334476,"score_spread":0.2658248303152291,"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."}}