{"id":"W7098526103","doi":"","title":"Cancer Registries Canadian Cancer Registry Manuals User Guide to Data Quality Reports for Provincial/Territorial Cancer Registries by","year":2005,"lang":"en","type":"article","venue":"","topic":"Bioenergy crop production and management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Cancer; Cancer registry; Data quality; Quality (philosophy); Patient data; MEDLINE","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0158279,0.001574325,0.002019487,0.0179466,0.00222726,0.004233639,0.003853653,0.001125533,0.1454233],"category_scores_gemma":[0.08110654,0.002520103,0.00228105,0.033827,0.0006571919,0.001932085,0.001775221,0.002251901,0.07509605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01827202,"about_ca_system_score_gemma":0.07783841,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8703275,"about_ca_topic_score_gemma":0.8921537,"domain_scores_codex":[0.984158,0.002573514,0.003848342,0.0007732118,0.007325287,0.001321598],"domain_scores_gemma":[0.892743,0.02101603,0.005945792,0.00677345,0.07159732,0.0019244],"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":[0.00002725077,0.00001231304,0.001185764,0.0003516615,0.00001511792,0.00001299005,0.00007103099,0.0001338496,0.00004619361,0.0004974607,0.981151,0.01649535],"study_design_scores_gemma":[0.0001960458,0.00001722567,0.01965629,0.000746053,0.00008178854,0.00009578222,0.000190804,0.0005627433,0.0002997461,0.0006782904,0.977393,0.00008220776],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0006159174,0.0007936509,0.004289549,0.001534302,0.0003542085,0.002316989,0.9580891,0.003457698,0.02854871],"genre_scores_gemma":[0.004910367,0.00321681,0.03620129,0.00125207,0.0001760615,0.005976093,0.8754529,0.003045385,0.069769],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1454233,"threshold_uncertainty_score":0.4864894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04950923887315341,"score_gpt":0.3397558283022545,"score_spread":0.2902465894291011,"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."}}