{"id":"W4254888363","doi":"10.22541/au.159301639.90704061/v2","title":"Influence of Temperature on the Global Spread of COVID-19","year":2020,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration","keywords":"Vulnerability (computing); Coronavirus disease 2019 (COVID-19); Geography; East Asia; South asia; China; Medicine; Disease; Ancient history; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005007724,0.0002578657,0.0003479861,0.000511645,0.0002988694,0.0008406346,0.0001515084,0.000250408,0.00121737],"category_scores_gemma":[0.001523841,0.0001252341,0.0004673037,0.0007760082,0.0003075175,0.0005896841,0.0006074478,0.0004038138,0.0002652424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003602773,"about_ca_system_score_gemma":0.0003286729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006773895,"about_ca_topic_score_gemma":0.006274801,"domain_scores_codex":[0.9994392,0.0001860928,0.00004370725,0.0001278827,0.00008490043,0.0001181503],"domain_scores_gemma":[0.9992595,0.000189844,0.0002518129,0.00006365365,0.0001647857,0.00007035724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005650943,0.00003557347,0.9553654,0.0003312475,0.0004041968,0.0007739422,0.001096367,0.004124547,0.009700312,0.0007002475,0.0008035877,0.02609944],"study_design_scores_gemma":[0.000003756303,0.0001229098,0.9918782,0.00006893141,0.0001361078,0.0003937136,0.001021183,0.0009346671,0.001110438,0.0002793483,0.004031435,0.00001939917],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869416,0.004808643,0.0007228231,0.0003175088,0.00009244352,0.00001919271,0.001096211,0.00001553917,0.00598608],"genre_scores_gemma":[0.9973807,0.001555722,0.0002559216,0.0000423219,0.00004537611,0.000006846131,0.0003525233,0.00001029219,0.0003502265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006773895,"threshold_uncertainty_score":0.01346892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2502223634909992,"score_gpt":0.4441331699652753,"score_spread":0.1939108064742761,"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."}}