{"id":"W7034463842","doi":"","title":"Training for objective-based codes in Canada","year":2006,"lang":"en","type":"article","venue":"NPARC","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Training (meteorology); Code (set theory); Key (lock); Scheme (mathematics); Transition (genetics)","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":[0.008443475,0.0003156833,0.0001888565,0.001349371,0.006201948,0.003769106,0.001606821,0.00215029,0.01658938],"category_scores_gemma":[0.01466078,0.0004020318,0.0003233052,0.001222048,0.003651571,0.001547113,0.004096111,0.003646091,0.003973802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.051941,"about_ca_system_score_gemma":0.2274685,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8674902,"about_ca_topic_score_gemma":0.9385924,"domain_scores_codex":[0.9879357,0.00116246,0.0002315858,0.0004459597,0.007965658,0.002258655],"domain_scores_gemma":[0.9720759,0.001984888,0.0007932216,0.0006923566,0.01602529,0.008428265],"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":[0.0000789355,0.0003936117,0.01033924,0.0002501234,0.000007210656,0.0005349802,0.01561167,0.002302466,0.00499102,0.1359788,0.5898352,0.2396767],"study_design_scores_gemma":[0.00001504927,0.00005640192,0.01195191,0.0002288364,0.000002290067,0.00009851391,0.005076135,0.0009172367,0.001174264,0.003760358,0.976665,0.00005404076],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1043431,0.00192642,0.04386488,0.1618562,0.004314358,0.001187103,0.001350018,0.001330096,0.679828],"genre_scores_gemma":[0.3846938,0.002062804,0.04232706,0.02175765,0.0002871252,0.0005526909,0.001320099,0.000476042,0.5465227],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1325098,"threshold_uncertainty_score":0.37686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01224510550101373,"score_gpt":0.2296444299862112,"score_spread":0.2173993244851975,"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."}}