{"id":"W3116724179","doi":"10.1101/2020.12.22.20248712","title":"Content analysis and characterization of medical tweets during the early Covid-19 pandemic","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Ottawa Hospital; University of British Columbia; McMaster University; University of Ottawa","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Content analysis; Public health; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Social media; 2019-20 coronavirus outbreak; Psychology; Public relations; Political science; Medicine; Sociology; Computer science; Nursing; World Wide Web; Pathology; Social science; Disease; Infectious disease (medical specialty)","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":[],"consensus_categories":[],"category_scores_codex":[0.001679392,0.0002734921,0.0003411775,0.006787649,0.0008417291,0.001689374,0.0003265351,0.0005304615,0.002071173],"category_scores_gemma":[0.01885721,0.0001505968,0.0002838079,0.004950891,0.0004071204,0.00180599,0.001647742,0.0004535955,0.0009581553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007910994,"about_ca_system_score_gemma":0.0007396741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003154173,"about_ca_topic_score_gemma":0.003590109,"domain_scores_codex":[0.9981408,0.0006577677,0.0002942727,0.0002396,0.0004214003,0.0002460913],"domain_scores_gemma":[0.9823299,0.01163254,0.002768842,0.0004569514,0.002301314,0.000510457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002715046,0.0002663129,0.6621188,0.004857774,0.0002045131,0.00209588,0.0858936,0.001055889,0.02382363,0.003109287,0.03033948,0.1835198],"study_design_scores_gemma":[0.00004199627,0.0003095708,0.8736348,0.001004751,0.0001509724,0.001056056,0.05856773,0.006103381,0.006303783,0.001590832,0.05112018,0.0001159784],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.972615,0.0007074749,0.001526167,0.0009932599,0.0001270191,0.0003956437,0.01877608,0.0001023535,0.004756904],"genre_scores_gemma":[0.9731313,0.0008600047,0.005137856,0.0004012597,0.0002269597,0.0008132393,0.01654796,0.00007952287,0.00280188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006787649,"threshold_uncertainty_score":0.008881569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2463346020804316,"score_gpt":0.4276039200061227,"score_spread":0.1812693179256911,"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."}}