{"id":"W3155053879","doi":"10.2196/24796","title":"Machine Learning Methods for the Diagnosis of Chronic Obstructive Pulmonary Disease in Healthy Subjects: Retrospective Observational Cohort Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Chronic Obstructive Pulmonary Disease (COPD) Research","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"AstraZeneca","keywords":"Medicine; COPD; Retrospective cohort study; Vital capacity; Cohort; Cohort study; Pulmonary function testing; Asthma; Internal medicine; Physical therapy; Intensive care medicine; Diffusing capacity; Lung","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004508042,0.0004338095,0.000764661,0.001524712,0.0007944937,0.0009324285,0.0006810127,0.0009658994,0.001011916],"category_scores_gemma":[0.007683687,0.0005407667,0.0010913,0.001876279,0.0003489926,0.0006811107,0.0006176411,0.001097374,0.0003532614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004478301,"about_ca_system_score_gemma":0.000712355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00602387,"about_ca_topic_score_gemma":0.003806297,"domain_scores_codex":[0.9966844,0.001008869,0.0004729629,0.0008915677,0.0006581504,0.0002840974],"domain_scores_gemma":[0.9945146,0.001314954,0.002007106,0.0009464059,0.0007335925,0.0004832637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002100263,0.00009839577,0.9986051,0.00001620783,0.0001116859,0.00003319878,0.00002552843,0.00004301086,0.00007614168,0.00001401928,0.0001008571,0.0006659405],"study_design_scores_gemma":[0.00005917111,0.000299256,0.9977975,0.00001290138,0.0001280355,0.0002186476,0.0001139381,0.0009305067,0.00005316153,0.00004018779,0.0003368263,0.000009871696],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956244,0.0009130621,0.001058215,0.00005902097,0.000029019,0.0001426239,0.001848238,0.00001149045,0.0003139931],"genre_scores_gemma":[0.9964297,0.0003292936,0.0009381484,0.00006379265,0.00004287691,0.0002042323,0.001806359,0.000006933862,0.0001785937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00602387,"threshold_uncertainty_score":0.02384114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03947684835899852,"score_gpt":0.3934715443561415,"score_spread":0.3539946959971429,"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."}}