{"id":"W3137381400","doi":"10.1371/journal.pone.0241725","title":"A stacked ensemble method for forecasting influenza-like illness visit volumes at emergency departments","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Libin Cardiovascular Institute of Alberta; Alberta Health Services; University of Calgary","funders":"Alberta Health Services","keywords":"Staffing; Ensemble forecasting; Reliability (semiconductor); Computer science; Interval (graph theory); Envelope (radar); Statistics; Medicine; Emergency medicine; Operations research; Econometrics; Machine learning; Mathematics","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":[0.001461703,0.0008835496,0.0009927611,0.0008294659,0.0004339503,0.0007436012,0.0009019364,0.0005518234,0.0008517514],"category_scores_gemma":[0.003584956,0.0003030254,0.0008827039,0.0008174614,0.0001728911,0.001028404,0.000570101,0.0009997155,0.0002104241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005055637,"about_ca_system_score_gemma":0.00100723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03312636,"about_ca_topic_score_gemma":0.03259996,"domain_scores_codex":[0.9996026,0.0001265088,0.00002632541,0.00008365973,0.0001091943,0.00005178644],"domain_scores_gemma":[0.9988105,0.0005829794,0.0001107236,0.00008720399,0.0003478048,0.00006080862],"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":[0.00007771492,0.00003875955,0.005728839,0.00001975075,0.0001727512,0.00003731204,0.00003053347,0.9324023,0.001029562,0.0007700958,0.0008649621,0.05882742],"study_design_scores_gemma":[0.000001563163,0.00001359007,0.000531072,0.000002533321,0.00001186336,0.000003965734,0.000003961392,0.9987859,0.0001583867,0.0003934783,0.00008886748,0.000004808998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2201048,0.00109995,0.7739038,0.0003587436,0.0002215471,0.00005529759,0.0008926043,0.001044338,0.002318877],"genre_scores_gemma":[0.9071438,0.0003464038,0.089733,0.0001034054,0.0001375835,0.00005602859,0.001159518,0.00005649103,0.001263821],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03312636,"threshold_uncertainty_score":0.06586707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2248920755890482,"score_gpt":0.398284616335586,"score_spread":0.1733925407465378,"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."}}