{"id":"W4323836089","doi":"10.2196/40575","title":"Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis","year":2023,"lang":"en","type":"article","venue":"JMIR Infodemiology","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Minority Health and Health Disparities; National Cancer Institute; National Institutes of Health","keywords":"Misinformation; Social media; Disinformation; Pandemic; Public opinion; Rhetoric; Public health; Political science; Internet privacy; Computer science; Coronavirus disease 2019 (COVID-19); World Wide Web; Medicine; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004117744,0.0003022637,0.0004126543,0.004415428,0.001145857,0.001613085,0.0005424328,0.0005947007,0.004045325],"category_scores_gemma":[0.03449283,0.0003645901,0.0004649877,0.005288067,0.0007763014,0.002267785,0.00179324,0.0008827329,0.002342535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001096468,"about_ca_system_score_gemma":0.001030704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008883598,"about_ca_topic_score_gemma":0.01079724,"domain_scores_codex":[0.9976769,0.0009466622,0.0003059959,0.0002996693,0.0004690915,0.0003016437],"domain_scores_gemma":[0.967062,0.02274238,0.004105504,0.001387998,0.004247679,0.0004544928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006600894,0.0002802877,0.8598872,0.001108104,0.0001047721,0.0006585281,0.0673243,0.0006635431,0.004247587,0.002858978,0.01350119,0.04870534],"study_design_scores_gemma":[0.00003228369,0.0002691156,0.8676748,0.0005648046,0.0001672793,0.000388905,0.07863197,0.007895828,0.004723867,0.001702668,0.03784455,0.0001040275],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815758,0.0002630974,0.00178567,0.0006032353,0.00002671197,0.0002794236,0.01089039,0.00003241051,0.004543259],"genre_scores_gemma":[0.9799088,0.0003417869,0.002829328,0.000220112,0.00007879684,0.001125824,0.0129185,0.00006478159,0.002512139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008883598,"threshold_uncertainty_score":0.02177697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05376169837555905,"score_gpt":0.3442570431983732,"score_spread":0.2904953448228142,"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."}}