{"id":"W4385851222","doi":"10.2196/46620","title":"Altmetric Analysis of Dermatology Manuscript Dissemination During the COVID-19 Era: Cross-Sectional Study","year":2023,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bibliometrics; Altmetrics; Impact factor; Coronavirus disease 2019 (COVID-19); Citation; MEDLINE; Logistic regression; Social media; Medicine; Library science; Computer science; Pathology; Political science; World Wide Web; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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","scholarly_communication"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01494723,0.0003352076,0.0007005121,0.0105755,0.0009485101,0.002980992,0.001168773,0.0008079511,0.003211716],"category_scores_gemma":[0.06242019,0.0003848253,0.001168354,0.01697364,0.000864493,0.003405935,0.002000929,0.001165716,0.0008785764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001248825,"about_ca_system_score_gemma":0.001423716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002429885,"about_ca_topic_score_gemma":0.002047825,"domain_scores_codex":[0.9864144,0.003580004,0.003939981,0.001641371,0.003666653,0.0007575628],"domain_scores_gemma":[0.8512419,0.0317408,0.09100692,0.005360365,0.01551535,0.00513469],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001172231,0.00008195204,0.9953293,0.0001608134,0.000151858,0.00003143807,0.0003549077,0.00004815002,0.0000622782,0.00006253882,0.0004588125,0.003140736],"study_design_scores_gemma":[0.000007121435,0.0001525377,0.997918,0.0000400553,0.0000603649,0.0001741955,0.0006548735,0.0001705125,0.00006736028,0.00005432896,0.000688622,0.00001198688],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898831,0.002708987,0.0005278215,0.0003589646,0.00006130201,0.0001417094,0.004327094,0.00003982908,0.001951318],"genre_scores_gemma":[0.9969615,0.0005294117,0.0004389168,0.00008450384,0.0001074429,0.0001296185,0.001362794,0.00001560041,0.0003702404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9894245,"threshold_uncertainty_score":0.07904947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1060942902764539,"score_gpt":0.4784285323769872,"score_spread":0.3723342421005333,"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."}}