{"id":"W2889174060","doi":"10.1101/401745","title":"Development and validation of the Evaluation Platform In COPD (EPIC): a population-based outcomes model of COPD for Canada","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Chronic Obstructive Pulmonary Disease (COPD) Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Coastal Health; Statistics Canada; University of British Columbia","funders":"Canadian Institutes of Health Research; Reseau canadien de recherche respiratoire; Michael Smith Health Research BC; Genome Canada","keywords":"COPD; Medicine; Natural history; EPIC; Population; Comorbidity; Mortality rate; Intensive care medicine; Physical therapy; Environmental health; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002971472,0.0008205422,0.0005373739,0.001010069,0.001158978,0.001485351,0.002472434,0.0007191059,0.003689877],"category_scores_gemma":[0.009141596,0.0004096463,0.001115575,0.001132598,0.0007559605,0.0004582941,0.0012973,0.001302556,0.0003538509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0214186,"about_ca_system_score_gemma":0.0535415,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.961791,"about_ca_topic_score_gemma":0.9276376,"domain_scores_codex":[0.9990476,0.0003367874,0.00004303493,0.000138021,0.0002714159,0.0001631397],"domain_scores_gemma":[0.9959461,0.001111733,0.0001942028,0.0001307654,0.002262152,0.000354968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001186201,0.00005773208,0.01988615,0.00007739462,0.00008661209,0.00008637782,0.0001180163,0.9546887,0.0001345795,0.009730363,0.007076972,0.007938586],"study_design_scores_gemma":[0.00009674753,0.00002850675,0.004848434,0.0000411184,0.00004275552,0.00001766449,0.00007379626,0.9865299,0.0001317681,0.002747013,0.005408898,0.0000333596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5163213,0.001088021,0.3554999,0.007419796,0.0004305417,0.002576825,0.06180175,0.003336286,0.05152552],"genre_scores_gemma":[0.86861,0.0005647034,0.1090697,0.0005139798,0.00004050996,0.0009454013,0.01432981,0.0002551069,0.005670807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03820902,"threshold_uncertainty_score":0.1554036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04177095098810562,"score_gpt":0.2895435657787062,"score_spread":0.2477726147906005,"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."}}