{"id":"W3008725318","doi":"10.2196/13075","title":"Peak Outpatient and Emergency Department Visit Forecasting for Patients With Chronic Respiratory Diseases Using Machine Learning Methods: Retrospective Cohort Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emergency department; Medicine; Retrospective cohort study; Emergency medicine; Cohort; Outpatient clinic; Medical emergency; Respiratory system; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001900899,0.000452582,0.0005268064,0.001100068,0.0004888179,0.0007621276,0.0006599287,0.0006577292,0.0008250181],"category_scores_gemma":[0.003258239,0.0005205113,0.001457627,0.001295626,0.0002138129,0.0007279404,0.0005610575,0.001091011,0.0001912527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005377808,"about_ca_system_score_gemma":0.0006274463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01075396,"about_ca_topic_score_gemma":0.01157338,"domain_scores_codex":[0.9990553,0.0001943517,0.0001306145,0.0003390182,0.0001346947,0.0001459797],"domain_scores_gemma":[0.9980407,0.0004829461,0.0006195276,0.0003461585,0.0002774938,0.0002332312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009607342,0.00003647583,0.9987142,0.00001075924,0.00009036252,0.00003310293,0.00002640782,0.00008957709,0.00004977815,0.00001252233,0.0001235105,0.0007172441],"study_design_scores_gemma":[0.00002220104,0.0001313986,0.9951923,0.00001861379,0.0001481023,0.0001435455,0.0002304571,0.003741642,0.000070038,0.00004461841,0.0002449572,0.00001208676],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977246,0.0003217664,0.0005331043,0.00004634613,0.00001416051,0.00003090175,0.001183533,0.000006225854,0.0001394148],"genre_scores_gemma":[0.9976581,0.0001726373,0.0003476733,0.00002800426,0.00001916841,0.00003963859,0.001645522,0.00000387449,0.00008544104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01075396,"threshold_uncertainty_score":0.02138275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03752055049348144,"score_gpt":0.3242581136832026,"score_spread":0.2867375631897212,"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."}}