{"id":"W4318305245","doi":"10.1016/j.jaip.2023.01.017","title":"Diagnostic Performance of a Machine Learning Algorithm (Asthma/Chronic Obstructive Pulmonary Disease [COPD] Differentiation Classification) Tool Versus Primary Care Physicians and Pulmonologists in Asthma, COPD, and Asthma/COPD Overlap","year":2023,"lang":"en","type":"article","venue":"The Journal of Allergy and Clinical Immunology In Practice","topic":"Chronic Obstructive Pulmonary Disease (COPD) Research","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto","funders":"Efficacy and Mechanism Evaluation Programme; Novartis Pharma; University of Ioannina; Grifols; Eisai; Covis Pharma; AstraZeneca; CSL Behring; Chiesi Farmaceutici; Sanofi; Mylan; GlaxoSmithKline; Regeneron Pharmaceuticals; Novo Nordisk; Teva Pharmaceutical Industries; AKL Research and Development; Novartis Pharmaceuticals Corporation; Pfizer","keywords":"Pulmonologists; Medicine; COPD; Asthma; Internal medicine; Medical diagnosis; Intensive care medicine; Algorithm; Physical therapy; Radiology","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":[0.02436567,0.0005235032,0.0008600688,0.002649335,0.0004635542,0.001573084,0.0007351433,0.001393866,0.0007847658],"category_scores_gemma":[0.09045408,0.0002522302,0.001023568,0.001226004,0.0009076488,0.0008821284,0.001311099,0.0007597643,0.0002745321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008510415,"about_ca_system_score_gemma":0.0006002091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002757387,"about_ca_topic_score_gemma":0.002896829,"domain_scores_codex":[0.9778161,0.01318603,0.001859945,0.003227607,0.00311844,0.0007918678],"domain_scores_gemma":[0.9093747,0.06954596,0.008368791,0.004271752,0.006255669,0.002183043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00119159,0.00006455342,0.9848519,0.00005504302,0.0003178995,0.00006410026,0.0001585548,0.001644686,0.0002655617,0.00009767374,0.0003419131,0.01094648],"study_design_scores_gemma":[0.0002801876,0.001969683,0.9269138,0.0001615589,0.0007620778,0.001456479,0.0005828188,0.06342794,0.002739502,0.0006279397,0.00101509,0.00006285439],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994531,0.001223347,0.00207499,0.0002353703,0.00005977422,0.00004337149,0.0003624436,0.00002960888,0.001440242],"genre_scores_gemma":[0.9981418,0.00008347647,0.001372743,0.00005666882,0.00003107038,0.000009743257,0.0002499228,0.00000305422,0.00005169438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02436567,"threshold_uncertainty_score":0.1288595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02095470424796284,"score_gpt":0.320525347585667,"score_spread":0.2995706433377042,"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."}}