{"id":"W4413043028","doi":"10.1183/23120541.00570-2025","title":"Risk stratification as a guide to goal-oriented management of patients with fibrotic interstitial lung disease: a registry-based analysis","year":2025,"lang":"en","type":"article","venue":"ERJ Open Research","topic":"Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Toronto; University of Saskatchewan; Centre Hospitalier de l’Université de Montréal; University of Calgary; McGill University; University of British Columbia","funders":"Boehringer Ingelheim","keywords":"Medicine; Idiopathic pulmonary fibrosis; Cohort; Body mass index; Interstitial lung disease; Internal medicine; Population; Vital capacity; Psychological intervention; Intensive care medicine; Emergency medicine; Physical therapy; Diffusing capacity; Lung; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007003888,0.0001657892,0.0003629222,0.0006473062,0.0002061267,0.0001191156,0.0005259981,0.00005027532,0.0004015166],"category_scores_gemma":[0.0002243378,0.0001362255,0.0001655581,0.002382266,0.0001654308,0.0001190152,0.0003604897,0.0002397046,0.0000331231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00036097,"about_ca_system_score_gemma":0.000578834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001336293,"about_ca_topic_score_gemma":0.00005880112,"domain_scores_codex":[0.9973541,0.0002527054,0.0004316339,0.0005917061,0.0009941875,0.0003756092],"domain_scores_gemma":[0.9975469,0.00008468234,0.0001105229,0.0009957929,0.00089532,0.0003668474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.2167559,0.005611318,0.6633102,0.005093849,0.007458694,0.0005345687,0.000348657,0.002065098,0.0003624414,0.02605757,0.06374496,0.00865675],"study_design_scores_gemma":[0.005095914,0.004044008,0.9578077,0.003965335,0.003740615,3.576218e-7,0.0008410261,0.01362858,0.0003455612,0.000169336,0.01003366,0.0003279579],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8817566,0.0002805676,0.03757267,0.004672556,0.0001940047,0.01114306,0.001053624,0.00007292433,0.06325397],"genre_scores_gemma":[0.9874489,0.00001376632,0.001977399,0.0001339932,0.00002507638,0.0003747818,0.0006403092,0.00001711241,0.009368688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2944975,"threshold_uncertainty_score":0.5555116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01417112004349646,"score_gpt":0.378122185467347,"score_spread":0.3639510654238506,"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."}}