{"id":"W2970413429","doi":"10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a1451","title":"Derivation and Validation of a Diagnostic Prediction Model for Interstitial Lung Disease","year":2019,"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":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Computer science; Interstitial lung disease; Model validation; Disease; Lung; Artificial intelligence; Medicine; Pathology; Data science; 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":[0.006246005,0.0008250374,0.0009538484,0.001967872,0.0006536063,0.001966488,0.001353132,0.001272749,0.001486993],"category_scores_gemma":[0.01670985,0.0004091813,0.000836411,0.0006680141,0.0003943541,0.0007013849,0.001046278,0.001259514,0.000773783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008860045,"about_ca_system_score_gemma":0.002037509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007174045,"about_ca_topic_score_gemma":0.004336595,"domain_scores_codex":[0.9984819,0.0005918887,0.0001533107,0.0002808527,0.0003591315,0.0001328839],"domain_scores_gemma":[0.9907227,0.006297346,0.0004563699,0.0004020272,0.00189053,0.0002311121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0008598723,0.001127412,0.2095127,0.0001935888,0.0006454817,0.001021202,0.0001870065,0.4553677,0.006866083,0.005641507,0.00902317,0.3095542],"study_design_scores_gemma":[0.00002498544,0.00006918903,0.0058132,0.00002130543,0.00005403555,0.0001381316,0.00001871178,0.9910721,0.0009227535,0.00144084,0.0004152241,0.000009565297],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3445387,0.0007044905,0.6450498,0.001970042,0.0002444595,0.0004837037,0.00206117,0.001632618,0.003315112],"genre_scores_gemma":[0.9161787,0.0001419373,0.08059915,0.0001520655,0.00007183614,0.0002016834,0.001747236,0.00003892129,0.0008685205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007174045,"threshold_uncertainty_score":0.03303242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009810196677130808,"score_gpt":0.2532121169412842,"score_spread":0.2434019202641534,"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."}}