{"id":"W4385544403","doi":"10.1016/j.ijoa.2023.103918","title":"Analysis of Twitter conversations in obstetric anesthesiology using the hashtag #OBAnes during the onset of the COVID-19 pandemic","year":2023,"lang":"en","type":"article","venue":"International Journal of Obstetric Anesthesia","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Coronavirus disease 2019 (COVID-19); Pandemic; Anesthesiology; Categorization; Observational study; 2019-20 coronavirus outbreak; Social media; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Obstetric anesthesia; Medical emergency; Anesthesia; Pregnancy; World Wide Web; Internal medicine; Computer science; Artificial intelligence; Virology","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00054178,0.0002576451,0.0002420419,0.001232373,0.0007651545,0.001189786,0.0002556267,0.0008607247,0.002830163],"category_scores_gemma":[0.005357406,0.0001388948,0.0002337076,0.0012569,0.0002547899,0.001269492,0.001132981,0.0007461473,0.001516407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000390546,"about_ca_system_score_gemma":0.0004326012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00686984,"about_ca_topic_score_gemma":0.01104514,"domain_scores_codex":[0.9993384,0.0002430246,0.00005837789,0.0001049735,0.0001179017,0.0001371811],"domain_scores_gemma":[0.995629,0.002487873,0.0007518296,0.0001391446,0.0005607854,0.0004314785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001378594,0.0002904503,0.8258374,0.0009205074,0.0002067952,0.001253772,0.04354188,0.001113165,0.01295923,0.002238805,0.0386916,0.0715678],"study_design_scores_gemma":[0.00001880357,0.0001992911,0.892269,0.0002696413,0.00009309078,0.0004877913,0.05718117,0.007533716,0.002321784,0.0006288813,0.03891738,0.00007952822],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815012,0.0003213492,0.000506816,0.001369119,0.0001818968,0.00005837459,0.009440278,0.00008230231,0.006538686],"genre_scores_gemma":[0.9906554,0.0002671745,0.0006542659,0.0003645114,0.0001909696,0.0001006246,0.004963516,0.00003713055,0.002766448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9987676,"threshold_uncertainty_score":0.01365972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1538075563061901,"score_gpt":0.4127676536144059,"score_spread":0.2589600973082158,"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."}}