{"id":"W4398132461","doi":"10.1016/j.resinv.2024.05.010","title":"Computed tomography machine learning classifier correlates with mortality in interstitial lung disease","year":2024,"lang":"en","type":"article","venue":"Respiratory Investigation","topic":"Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Interstitial lung disease; Computed tomography; Classifier (UML); Lung; Radiology; Artificial intelligence; Internal medicine","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":[0.001108852,0.0004489188,0.00047885,0.001258207,0.0003988319,0.001472912,0.0005774571,0.00119121,0.002786373],"category_scores_gemma":[0.01055648,0.0002515237,0.000476941,0.0006969516,0.000430933,0.000707465,0.0003914308,0.001106534,0.0007750028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003658611,"about_ca_system_score_gemma":0.0003688169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00240613,"about_ca_topic_score_gemma":0.002704035,"domain_scores_codex":[0.9993526,0.0001899439,0.00008807705,0.0001166687,0.0001230978,0.0001296712],"domain_scores_gemma":[0.9923152,0.003483903,0.002025273,0.000431508,0.001068278,0.0006757808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001811693,0.00004959303,0.9971089,0.000005452927,0.00004094831,0.0000705924,0.00001273619,0.0002017525,0.0003553456,0.0000240108,0.0002364084,0.001713216],"study_design_scores_gemma":[0.000009809866,0.0001357339,0.991288,0.00001803296,0.00008569592,0.0005242692,0.0001387138,0.006695777,0.0005963002,0.0001999947,0.0002983944,0.000009299467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970778,0.0005458913,0.0004703692,0.0002425642,0.00005570018,0.000006716908,0.0004211828,0.00002824175,0.001151443],"genre_scores_gemma":[0.9988181,0.00009797512,0.0001959081,0.00004076537,0.00008364184,0.000004112028,0.0003988164,0.000005138138,0.0003555017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002786373,"threshold_uncertainty_score":0.009321332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02094478957761099,"score_gpt":0.2695827865545795,"score_spread":0.2486379969769685,"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."}}