{"id":"W3083279630","doi":"10.1101/2020.09.04.20188771","title":"COVID-19 Preprints and Their Publishing Rate: An Improved Method","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Preprint; Upload; Context (archaeology); Computer science; Coronavirus disease 2019 (COVID-19); Scientific publishing; World Wide Web; Server; Publishing; Data science; Infectious disease (medical specialty); Medicine; Geography; Disease; Literature; Art","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.03810269,0.001676019,0.002135559,0.01567496,0.001530255,0.009282302,0.004497156,0.003462421,0.0100582],"category_scores_gemma":[0.170137,0.001055159,0.003261826,0.01159839,0.001476884,0.005191171,0.003580634,0.002894633,0.009864674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00170153,"about_ca_system_score_gemma":0.00433664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006151753,"about_ca_topic_score_gemma":0.004805792,"domain_scores_codex":[0.9637264,0.01212872,0.006317867,0.008856055,0.007998773,0.0009721591],"domain_scores_gemma":[0.8498143,0.08870388,0.01022201,0.03002509,0.01965053,0.001584188],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002562007,0.000880482,0.2247342,0.002875908,0.001950552,0.0007455054,0.001094209,0.01882827,0.006210777,0.01624835,0.08337803,0.6404917],"study_design_scores_gemma":[0.0009003226,0.0004622669,0.07667782,0.0007310997,0.0009025509,0.002275955,0.0009487887,0.7662982,0.01526616,0.03892295,0.09602606,0.0005877123],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06888044,0.004834649,0.8362365,0.002935215,0.002071187,0.002846959,0.04371008,0.03221033,0.006274591],"genre_scores_gemma":[0.2127781,0.001117176,0.7213789,0.0004955704,0.001758207,0.002799708,0.0507416,0.003128884,0.005801997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9843251,"threshold_uncertainty_score":0.2015087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2152926009066877,"score_gpt":0.4552273630391432,"score_spread":0.2399347621324555,"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."}}