{"id":"W3158142982","doi":"10.1101/2021.04.25.21256069","title":"Reliability of COVID-19 data: An evaluation and reflection","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; Temple University; George Washington University","keywords":"Coronavirus disease 2019 (COVID-19); Reliability (semiconductor); Statistics; 2019-20 coronavirus outbreak; Case fatality rate; Medicine; Outbreak; Demography; Geography; Environmental health; Computer science; Mathematics; Disease","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.5476258,0.0008805026,0.001148644,0.005503368,0.001594268,0.008031091,0.00345421,0.001581078,0.001518761],"category_scores_gemma":[0.7617469,0.0008083139,0.002002976,0.005469588,0.005956758,0.005390457,0.005502775,0.00273748,0.0005045728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007990768,"about_ca_system_score_gemma":0.005818625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006348741,"about_ca_topic_score_gemma":0.002893214,"domain_scores_codex":[0.4454712,0.4137769,0.0278885,0.01452416,0.09573138,0.002607932],"domain_scores_gemma":[0.1141424,0.6962379,0.03833574,0.04263222,0.1071027,0.001549034],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0022961,0.0006919584,0.6919193,0.002183968,0.00209565,0.0002906503,0.03034443,0.01528391,0.001759763,0.02852733,0.01657159,0.2080354],"study_design_scores_gemma":[0.0007527631,0.005621305,0.5842441,0.007551002,0.002222831,0.00122171,0.02858869,0.2214077,0.02008021,0.04728084,0.08031804,0.0007107185],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7024027,0.004092224,0.2279637,0.02050879,0.0009344044,0.004521655,0.005319496,0.001055138,0.03320192],"genre_scores_gemma":[0.9521343,0.0003459078,0.04378676,0.0007963071,0.0001516777,0.0009449728,0.001107236,0.0001854305,0.000547415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4523742,"threshold_uncertainty_score":0.5578579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335382003001439,"score_gpt":0.430648855130127,"score_spread":0.2971106548299831,"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."}}