{"id":"W4367599626","doi":"10.1164/ajrccm-conference.2023.207.1_meetingabstracts.a6540","title":"Chest Computed Tomography Machine Learning Classifier for Idiopathic Pulmonary Fibrosis Predicts Mortality in Interstitial Lung Diseases","year":2023,"lang":"en","type":"article","venue":"","topic":"Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Idiopathic pulmonary fibrosis; Computed tomography; Medicine; Pulmonary fibrosis; Lung; Radiology; Classifier (UML); Computer science; 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":[0.00097605,0.0004895488,0.0006236255,0.00149672,0.000382546,0.001120261,0.0005706556,0.001170042,0.002856504],"category_scores_gemma":[0.005613182,0.0001763966,0.0006787103,0.0004167244,0.0002583266,0.0006336349,0.0004272586,0.0008488638,0.0008308087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002900317,"about_ca_system_score_gemma":0.0003502177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001961089,"about_ca_topic_score_gemma":0.002732908,"domain_scores_codex":[0.9995056,0.0001199937,0.00007006158,0.0000940899,0.0001082903,0.0001018486],"domain_scores_gemma":[0.9969882,0.001394175,0.0005567322,0.000159888,0.00050264,0.0003983926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003753524,0.0001157807,0.9907939,0.0000159769,0.00006533226,0.000167666,0.00001533467,0.0005675578,0.000873773,0.00004526673,0.0008266065,0.006137381],"study_design_scores_gemma":[0.00004872886,0.0003235874,0.9485589,0.00006075524,0.0002125778,0.001143477,0.0002218722,0.0468615,0.001471488,0.0003719368,0.0007060851,0.00001910588],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955292,0.0007559222,0.00101919,0.0003043319,0.00009198415,0.00001788457,0.0009500922,0.00005325229,0.001278139],"genre_scores_gemma":[0.9977251,0.0001239169,0.0005284768,0.00004983263,0.0001072707,0.000009569088,0.001083271,0.000004609004,0.0003680444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002856504,"threshold_uncertainty_score":0.009555936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02102245352005974,"score_gpt":0.2791833440044836,"score_spread":0.2581608904844239,"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."}}