{"id":"W3114604168","doi":"10.21203/rs.3.rs-132274/v1","title":"Epidemic Curves and COVID-19: How to Reduce The Confusion","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University; University of Ottawa","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Confusion; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Virology; Geography; Psychology; Medicine; Outbreak","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.09946561,0.003501616,0.00472011,0.01214657,0.00409881,0.02138693,0.007750232,0.007803341,0.01742421],"category_scores_gemma":[0.4610949,0.00203536,0.003208471,0.01097956,0.01802523,0.05439775,0.01017416,0.01832936,0.006991655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009989421,"about_ca_system_score_gemma":0.01171384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03212615,"about_ca_topic_score_gemma":0.01589099,"domain_scores_codex":[0.9305502,0.0522594,0.004280781,0.003723888,0.008435812,0.0007499071],"domain_scores_gemma":[0.5941822,0.3103383,0.01303863,0.03078226,0.04601423,0.005644326],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003445753,0.0001003853,0.009447667,0.00204504,0.0005973165,0.0003661971,0.005131415,0.00518233,0.0001697782,0.338332,0.4382618,0.2000215],"study_design_scores_gemma":[0.00008777598,0.00006013523,0.002446823,0.003384532,0.0001117287,0.0002804886,0.002801732,0.005824676,0.0002136836,0.6629099,0.3216565,0.0002220441],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004518483,0.05477825,0.2372579,0.6464169,0.03913041,0.0003696419,0.002452222,0.002704599,0.01237158],"genre_scores_gemma":[0.1573806,0.08280611,0.562812,0.09928107,0.07424763,0.001957813,0.003920152,0.005920789,0.01167392],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9005344,"threshold_uncertainty_score":0.5260307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6474666936453305,"score_gpt":0.5847152110257211,"score_spread":0.06275148261960939,"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."}}