{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00098145,0.000149762,0.0004160315,0.0005727963,0.0004430804,0.0000623921,0.0002177195,0.0002797235,0.0008258969],"category_scores_gemma":[0.0006268444,0.0001404397,0.0001301467,0.00255231,0.00001359446,0.0003550939,0.0001057776,0.0002329501,0.0001551843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00018836,"about_ca_system_score_gemma":0.00008143722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001804429,"about_ca_topic_score_gemma":0.001535603,"domain_scores_codex":[0.9982802,0.0003059627,0.0003236926,0.0003941002,0.0001915972,0.0005044428],"domain_scores_gemma":[0.9989647,0.0002816981,0.0001624066,0.0002513762,0.0001966675,0.0001431892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001077617,0.00001526981,0.9443274,0.000006645484,0.0001222716,0.00000788277,0.00381611,0.00001484025,0.00001656369,0.02980241,0.02107739,0.0007825068],"study_design_scores_gemma":[0.0002674867,0.00004884811,0.965436,0.000002668583,0.00007518478,7.81845e-7,0.0004309945,0.0003380931,0.000002391688,0.01931592,0.01392543,0.0001562409],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9639006,0.0002493228,0.0003133622,0.0190575,0.0002240241,0.0003046331,0.000005073113,0.0003108682,0.01563458],"genre_scores_gemma":[0.9953451,0.0004593846,0.00007053199,0.0007621376,0.0003446017,0.00008993486,0.0000315962,0.00001047001,0.002886259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03144445,"threshold_uncertainty_score":0.9042993,"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."}}