{"id":"W3111190599","doi":"10.23889/ijpds.v5i5.1477","title":"British Columbia’s Health Data Platform: Unleashing the Power of a Data Environment Commons for Health and Health System Improvement","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Health","funders":"Economic and Social Research Council","keywords":"Transparency (behavior); Data governance; Data quality; Data sharing; Information privacy; Data security; Data management; Agile software development; Computer science; Business; Data science; Computer security; Database; Medicine; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.02078112,0.0006429551,0.0004715334,0.002030078,0.01368615,0.0259009,0.003410349,0.005003065,0.02717087],"category_scores_gemma":[0.03245216,0.000695301,0.0006310167,0.004840916,0.01041998,0.007054313,0.0156838,0.008530511,0.005517706],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0579856,"about_ca_system_score_gemma":0.2233141,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8141311,"about_ca_topic_score_gemma":0.8639766,"domain_scores_codex":[0.9768379,0.006189772,0.0007263524,0.001909937,0.01067873,0.003657274],"domain_scores_gemma":[0.9546992,0.01109792,0.0008352285,0.005154642,0.01304245,0.01517056],"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":[0.00005861037,0.00004164238,0.003588494,0.000267365,0.00002284569,0.0002535485,0.0029004,0.0005900277,0.0005040279,0.06806166,0.8502585,0.07345289],"study_design_scores_gemma":[0.0000175641,0.00001231771,0.003702035,0.0005009022,0.000006940944,0.00005373979,0.003028168,0.0005440767,0.0002739053,0.01304044,0.9787804,0.00003950871],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01223115,0.004418926,0.006906429,0.820972,0.003379368,0.0002632256,0.006317616,0.001231447,0.1442798],"genre_scores_gemma":[0.297275,0.01544897,0.09905653,0.245822,0.003135626,0.0008556219,0.01912975,0.002424056,0.3168525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9420144,"threshold_uncertainty_score":0.420717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2740117676628542,"score_gpt":0.4917033593266383,"score_spread":0.2176915916637842,"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."}}