{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.009781666,0.0001247996,0.0004293414,0.00008015724,0.002507856,0.0003220286,0.005046284,0.00004626622,0.00005682974],"category_scores_gemma":[0.000686313,0.0001250115,0.00003358732,0.0001657505,0.0001379933,0.002883782,0.003603481,0.0004297385,0.000002334261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00122827,"about_ca_system_score_gemma":0.005413152,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03245697,"about_ca_topic_score_gemma":0.02828261,"domain_scores_codex":[0.9956494,0.0001679354,0.001702512,0.0007496843,0.00110324,0.0006272523],"domain_scores_gemma":[0.9953409,0.0004071184,0.001943729,0.001461938,0.0002349926,0.0006112954],"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":[0.0001345821,0.00008991669,0.05168825,0.0009919873,0.00008828298,0.000001683238,0.002101928,0.0000260034,0.00001064837,0.002116656,0.8052578,0.1374923],"study_design_scores_gemma":[0.003859021,0.001215805,0.1342877,0.001174479,0.00002989991,0.0001004187,0.009912297,0.06853951,3.869529e-7,0.0006103964,0.779916,0.0003540945],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02074449,0.003647909,0.1428738,0.7409715,0.006503094,0.008141068,0.07689331,0.0001125486,0.0001122922],"genre_scores_gemma":[0.798888,0.002857565,0.0377617,0.13115,0.001608247,0.00009945295,0.02736836,0.00006885405,0.000197848],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.7781435,"threshold_uncertainty_score":0.9987907,"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."}}