{"id":"W4403258249","doi":"10.1177/21582440241286217","title":"Research Output, Key Topics, and Trends in Productivity, Visibility, and Collaboration in Social Sciences Research on COVID-19: A Scientometric Analysis and Visualization","year":2024,"lang":"en","type":"article","venue":"SAGE Open","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Visibility; Productivity; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Visualization; Data science; Key (lock); Regional science; Sociology; Computer science; Geography; Economics; Economic growth; Biology; Medicine; Virology; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.04714728,0.001430849,0.004162774,0.1746882,0.002724094,0.01123542,0.001394175,0.001170595,0.006388405],"category_scores_gemma":[0.2071432,0.0007113283,0.00400373,0.2713115,0.002183226,0.006087828,0.009299271,0.001465756,0.0008353346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005076197,"about_ca_system_score_gemma":0.01116902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008131867,"about_ca_topic_score_gemma":0.007565957,"domain_scores_codex":[0.9452134,0.0171425,0.0135555,0.002877368,0.01897076,0.002240516],"domain_scores_gemma":[0.7472991,0.190268,0.01991482,0.008492941,0.03086577,0.003159274],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000796795,0.000278032,0.4595685,0.04728781,0.004673652,0.001060888,0.03160765,0.006638277,0.003940058,0.03947407,0.07095633,0.3337179],"study_design_scores_gemma":[0.0002975274,0.0004257821,0.6358801,0.009567316,0.00284696,0.001112809,0.03153953,0.0163424,0.002923908,0.03229862,0.2662708,0.0004942639],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6140611,0.02792761,0.03416265,0.00891144,0.001074846,0.00625462,0.243714,0.003677396,0.06021632],"genre_scores_gemma":[0.8036361,0.01496899,0.08591534,0.0003600688,0.0005565294,0.01195189,0.07846476,0.0006910002,0.003455393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9528527,"threshold_uncertainty_score":0.2493416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.791546586054148,"score_gpt":0.7291634070649856,"score_spread":0.06238317898916235,"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."}}