{"id":"W4229331796","doi":"10.12927/hcq.2022.26813","title":"Machine Learning Applied to Routinely Collected Health Administrative Data","year":2022,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario","funders":"","keywords":"Computer science; Data science; Machine learning; Artificial intelligence; Process management; Knowledge management; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01129597,0.001193859,0.001554027,0.004557837,0.000934707,0.003114878,0.001478451,0.001319562,0.001961617],"category_scores_gemma":[0.07943536,0.0006681108,0.001416115,0.007673732,0.00077053,0.001810779,0.001666906,0.003454417,0.001207482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001909622,"about_ca_system_score_gemma":0.003971036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01452546,"about_ca_topic_score_gemma":0.01072612,"domain_scores_codex":[0.9879665,0.007859534,0.0009935765,0.0009839545,0.001839562,0.0003569826],"domain_scores_gemma":[0.9625035,0.03083418,0.001437051,0.001977442,0.002947775,0.00030012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002098971,0.0005241417,0.07524341,0.001006651,0.001218065,0.000803743,0.0005836933,0.2929893,0.001245115,0.03513761,0.01815813,0.5728803],"study_design_scores_gemma":[0.00003102317,0.0001267345,0.009134021,0.0001895033,0.00005786286,0.0002058175,0.0002120046,0.9191625,0.0007720789,0.06196699,0.008104203,0.0000371536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07102159,0.00906343,0.8988749,0.008220402,0.001461043,0.0006188822,0.002549071,0.002485718,0.005704969],"genre_scores_gemma":[0.6144744,0.00894939,0.3659295,0.001232304,0.001634934,0.0009060765,0.003747365,0.0002457334,0.002880208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01452546,"threshold_uncertainty_score":0.05973953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07125663350019369,"score_gpt":0.3568292382445145,"score_spread":0.2855726047443208,"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."}}