{"id":"W3170121748","doi":"","title":"Research Guides: Government Documents - Canada: Forensic Sciences","year":2013,"lang":"en","type":"libguides","venue":"","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Forensic science; Library science; Political science; Data science; Geography; Computer science; Archaeology; Linguistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001319533,0.0003580794,0.0003295997,0.00008125122,0.0004182099,0.0001906109,0.001232415,0.0004277634,0.001152935],"category_scores_gemma":[0.0003719473,0.000277509,0.0001132491,0.0002679896,0.0009929107,0.000004186291,0.001110643,0.0004586464,0.0001247142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002865477,"about_ca_system_score_gemma":0.004052467,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5969596,"about_ca_topic_score_gemma":0.4718944,"domain_scores_codex":[0.9940993,0.0002174556,0.000451636,0.001012191,0.003077925,0.001141499],"domain_scores_gemma":[0.9982281,0.00008298112,0.000106501,0.0008570317,0.0004528023,0.0002726351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001414994,0.00001753013,0.0001934843,0.00005129423,0.00008793734,0.000008279955,0.000004507167,0.00001143105,0.0008321736,0.0002745213,0.992388,0.006116745],"study_design_scores_gemma":[0.0002149913,0.0004798246,0.0002447688,0.00006183057,0.000009592229,0.00001042292,0.0004060356,0.00002421433,0.02458866,0.0003376762,0.9732798,0.000342186],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03566198,0.01074092,0.00007843358,0.004174589,0.002247799,0.001600295,0.0003647404,0.00002029214,0.945111],"genre_scores_gemma":[0.03586576,0.004755049,0.002287346,0.001932013,0.00208447,0.0002249302,0.0006326,0.00009495997,0.9521229],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1250653,"threshold_uncertainty_score":0.9999677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04083053334814147,"score_gpt":0.3448816900237082,"score_spread":0.3040511566755667,"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."}}