{"id":"W3127292647","doi":"10.1101/2021.02.03.21250974","title":"Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of British Columbia; University of Victoria","funders":"Wellcome Trust","keywords":"Probabilistic logic; Staffing; Geospatial analysis; Actuarial science; Coronavirus disease 2019 (COVID-19); Probabilistic forecasting; Baseline (sea); Forecast skill; Statistical model; Operations research; Computer science; Econometrics; Business; Geography; Meteorology; Economics; Political science; Medicine; Engineering; Artificial intelligence","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":[0.005539234,0.001117159,0.0008972452,0.0009376326,0.0004152382,0.0009448882,0.0009499367,0.00090924,0.0007023076],"category_scores_gemma":[0.008506797,0.0004782394,0.0009787999,0.0006562468,0.0002677459,0.001220837,0.0009909426,0.001235252,0.0002383069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001392895,"about_ca_system_score_gemma":0.001969414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07467949,"about_ca_topic_score_gemma":0.04015577,"domain_scores_codex":[0.9989631,0.0004735596,0.00005961849,0.0002131753,0.0001758972,0.000114588],"domain_scores_gemma":[0.9963363,0.001923324,0.0002403222,0.0003061109,0.0008916963,0.0003021439],"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":[0.0003435124,0.0001835023,0.02782713,0.00003620822,0.0002123188,0.00004119805,0.00006290261,0.9515111,0.0004768661,0.0003843944,0.00185299,0.01706776],"study_design_scores_gemma":[0.00002244602,0.0001080505,0.003556701,0.00000990967,0.00002978439,0.000006537754,0.00003130097,0.995372,0.0003064985,0.0002723237,0.0002704344,0.00001395353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776995,0.0004996665,0.01417467,0.0009362111,0.0001747933,0.00008011027,0.002100362,0.0008357671,0.003498809],"genre_scores_gemma":[0.9931582,0.0001142237,0.004408377,0.00009465633,0.00003870447,0.00002812198,0.001856223,0.00002352783,0.0002780314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07467949,"threshold_uncertainty_score":0.1484896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5152404789777729,"score_gpt":0.4828004323958677,"score_spread":0.03244004658190519,"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."}}