{"id":"W2082302018","doi":"10.1001/jama.2013.393","title":"The Inevitable Application of Big Data to Health Care","year":2013,"lang":"en","type":"article","venue":"JAMA","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1676,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Otorhinolaryngology; Family medicine; Sign (mathematics); Psychiatry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0427602,0.001170447,0.001863066,0.004516054,0.002312069,0.01187895,0.003683061,0.004443238,0.01557101],"category_scores_gemma":[0.1602747,0.001562885,0.002319735,0.00713023,0.009044881,0.02541243,0.010888,0.01854015,0.00479768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005039632,"about_ca_system_score_gemma":0.005457994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005043373,"about_ca_topic_score_gemma":0.005989007,"domain_scores_codex":[0.9707928,0.01343499,0.001473391,0.003123283,0.01017111,0.001004376],"domain_scores_gemma":[0.8258343,0.1249793,0.006815442,0.02696934,0.009315056,0.00608655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001818856,0.0000847038,0.01140438,0.001937189,0.0006862699,0.0003584384,0.001514939,0.005417851,0.0005428396,0.2276023,0.5478578,0.2024114],"study_design_scores_gemma":[0.00005032438,0.00005390086,0.005190271,0.001409498,0.0000627001,0.0003991823,0.001540807,0.008868717,0.0003696335,0.5879747,0.3939491,0.0001311385],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.009165991,0.0372867,0.1032355,0.7689339,0.02032229,0.0003418187,0.01116611,0.002866243,0.0466815],"genre_scores_gemma":[0.3039116,0.07866567,0.2297285,0.3105277,0.04653018,0.001698552,0.01021875,0.002661175,0.01605785],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0427602,"threshold_uncertainty_score":0.2261403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04613789262909732,"score_gpt":0.3316804957360556,"score_spread":0.2855426031069583,"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."}}