{"id":"W3082051346","doi":"10.1007/s11192-020-03675-3","title":"Publishing volumes in major databases related to Covid-19","year":2020,"lang":"en","type":"article","venue":"Scientometrics","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"Wellcome Trust","keywords":"Scopus; Coronavirus disease 2019 (COVID-19); Web of science; Publishing; Pandemic; Library science; China; MEDLINE; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Bibliometrics; 2019-20 coronavirus outbreak; Analytics; History; Medicine; Database; Computer science; Political science; Disease; Infectious disease (medical specialty); Virology; Pathology","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":[0.009847582,0.003003362,0.006318618,0.1557337,0.001914024,0.01642543,0.002176478,0.002347981,0.05193015],"category_scores_gemma":[0.1404033,0.0008768836,0.002537496,0.3102295,0.001518679,0.006897502,0.00531737,0.002376469,0.02264784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003915939,"about_ca_system_score_gemma":0.01337286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005621353,"about_ca_topic_score_gemma":0.004902137,"domain_scores_codex":[0.9544817,0.003988954,0.02676904,0.003251281,0.00983375,0.001675404],"domain_scores_gemma":[0.8123209,0.0854467,0.0539315,0.007231197,0.031969,0.009100664],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001259418,0.00008988823,0.0233311,0.1579302,0.00189329,0.0009857082,0.002273209,0.0005974001,0.001192873,0.01711329,0.6548027,0.1385308],"study_design_scores_gemma":[0.0003141943,0.0000927303,0.04229163,0.0259636,0.0009913065,0.001344537,0.001556247,0.0003750009,0.001046305,0.007998092,0.917832,0.000194378],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.004990388,0.02916482,0.0005318701,0.002071754,0.0007713488,0.0004118158,0.9441121,0.001145015,0.01680085],"genre_scores_gemma":[0.02984823,0.07518923,0.007773052,0.0014217,0.002221877,0.002409931,0.8709741,0.0008901136,0.009271831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9901524,"threshold_uncertainty_score":0.1737237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2913286398736232,"score_gpt":0.4731993666241887,"score_spread":0.1818707267505655,"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."}}