{"id":"W4387957258","doi":"10.23889/ijpds.v8i4.2160","title":"Health Data Governance for Research Use in Alberta","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian VIGOUR Centre; Alberta Health Services; University of Alberta; University of Calgary","funders":"","keywords":"Custodians; Data governance; General partnership; Corporate governance; Analytics; Big data; Research ethics; Business; Data sharing; Data science; Medicine; Knowledge management; Data quality; Service (business); Computer science; Data mining; Geography; Alternative medicine; Marketing; Finance","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03653824,0.00007592488,0.0001811231,0.0005788539,0.0004358134,0.0004567993,0.004634443,0.00008009195,0.00002260754],"category_scores_gemma":[0.1724125,0.00006687429,0.00003498185,0.001171376,0.0003282395,0.00294737,0.002114649,0.0009960482,0.00003412706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005380329,"about_ca_system_score_gemma":0.002249532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004941518,"about_ca_topic_score_gemma":0.01786373,"domain_scores_codex":[0.9943221,0.00008253928,0.0007379661,0.0007530349,0.003530077,0.0005743481],"domain_scores_gemma":[0.983279,0.01211185,0.000268053,0.001673064,0.002339431,0.0003285376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001594296,0.000464074,0.4038964,0.0002198871,0.0000788299,0.00005999995,0.0003219889,0.0005445636,0.0005572864,0.3082843,0.1920092,0.09196921],"study_design_scores_gemma":[0.002026668,0.0002754318,0.5806135,0.0007416171,0.000004878637,0.00008113262,0.00008750316,0.2454163,0.0000235531,0.05488031,0.1157191,0.0001300435],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.324486,0.000223844,0.01490284,0.6349644,0.01081933,0.004295202,0.009659164,0.00009852122,0.0005506744],"genre_scores_gemma":[0.9618377,0.001581391,0.02270869,0.001199123,0.001138706,0.00003251748,0.004950653,0.00002978961,0.006521451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6373517,"threshold_uncertainty_score":0.996838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9164866338083132,"score_gpt":0.7551595823879634,"score_spread":0.1613270514203498,"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."}}