{"id":"W3118676337","doi":"","title":"Bibliometric Analysis of Worldwide Coronavirus Research based on Web of Science between 1970 and February 2020","year":2020,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Centrality; Betweenness centrality; Web of science; Bibliometrics; Social network analysis; Webometrics; Data science; Closeness; Library science; Citation; China; Geography; Coronavirus; Coronavirus disease 2019 (COVID-19); Pandemic; Descriptive statistics; Computer science; World Wide Web; Political science; Statistics; MEDLINE; Social media; Medicine; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002928107,0.0004791298,0.0009476542,0.1081168,0.0006990826,0.003662823,0.0005306289,0.0005067755,0.0036693],"category_scores_gemma":[0.02426399,0.0001562616,0.000940895,0.1351137,0.0004110376,0.002384542,0.001259865,0.0004091568,0.001338781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001822516,"about_ca_system_score_gemma":0.002313738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009486412,"about_ca_topic_score_gemma":0.01025648,"domain_scores_codex":[0.9931172,0.0007394574,0.001475185,0.0005440491,0.003771946,0.0003520469],"domain_scores_gemma":[0.9779809,0.009235555,0.006470349,0.0005655591,0.005076848,0.0006707424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002845261,0.0001294303,0.7718916,0.006925258,0.000852175,0.001165265,0.002797894,0.002300568,0.001588702,0.005085028,0.03133465,0.175645],"study_design_scores_gemma":[0.0000157036,0.00008163242,0.9306541,0.0008964991,0.0004682053,0.001305645,0.003004438,0.003703024,0.001259644,0.001377548,0.0571715,0.00006201152],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7476726,0.03225395,0.002319167,0.001963064,0.0003100781,0.0003104266,0.166548,0.0007142901,0.04790849],"genre_scores_gemma":[0.8981357,0.01598414,0.003013008,0.0001292655,0.0004114127,0.0003721781,0.07731289,0.00009765443,0.00454364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8918831,"threshold_uncertainty_score":0.01886237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7796599056086541,"score_gpt":0.6744480922062391,"score_spread":0.1052118134024149,"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."}}