{"id":"W4385178404","doi":"10.2196/preprints.41582","title":"Public Officials’ Engagement on Social Media During the Rollout of the COVID-19 Vaccine: Content Analysis of Tweets (Preprint)","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Government (linguistics); Jurisdiction; Political science; Coronavirus disease 2019 (COVID-19); Content analysis; Public engagement; Pandemic; Public opinion; Public relations; Politics; Sociology; Medicine; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0008458646,0.0002176102,0.0002454163,0.002129738,0.001496958,0.002028296,0.0003008245,0.0003948564,0.00273566],"category_scores_gemma":[0.008101271,0.0001334198,0.0002404445,0.003666697,0.0005380451,0.00100783,0.0009847648,0.0005494645,0.0008954548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002978816,"about_ca_system_score_gemma":0.002465582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3210938,"about_ca_topic_score_gemma":0.4486266,"domain_scores_codex":[0.9991252,0.0001767835,0.00005372119,0.0001072542,0.0003227101,0.0002143966],"domain_scores_gemma":[0.9924925,0.003567548,0.001172207,0.0002110378,0.002070404,0.0004862939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007031512,0.0001515906,0.7267171,0.00115212,0.0001144792,0.0007139525,0.1338581,0.0006727013,0.006767477,0.001897974,0.06106818,0.06618325],"study_design_scores_gemma":[0.000009970901,0.00005250587,0.8769121,0.0002301133,0.0000447858,0.00007761004,0.08263142,0.001823913,0.001346637,0.0003023222,0.03650397,0.00006460482],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618282,0.0002291617,0.0005271878,0.001666047,0.00008649343,0.0001962807,0.02748105,0.0000784584,0.007907053],"genre_scores_gemma":[0.9762571,0.0004896919,0.001933976,0.0005873495,0.0001382833,0.0004484328,0.01396593,0.0000769335,0.006102374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3210938,"threshold_uncertainty_score":0.6384495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2634036533706061,"score_gpt":0.377125518803929,"score_spread":0.113721865433323,"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."}}