{"id":"W4390065194","doi":"10.1093/geroni/igad104.0203","title":"EXAMINING COVID-19 VACCINE–RELATED AGEISM IN TWITTER DATA","year":2023,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Toronto; University of Saskatchewan; Thompson Rivers University","funders":"","keywords":"Misinformation; Thematic analysis; Social media; Blame; Coronavirus disease 2019 (COVID-19); Pandemic; Psychology; Medicine; Social psychology; Political science; Sociology; Qualitative research; Social science; 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":[0.003411976,0.0002551455,0.0001953989,0.001839047,0.001300429,0.001848918,0.0002823157,0.0006289027,0.003171009],"category_scores_gemma":[0.02461381,0.0001333508,0.0002065402,0.002005801,0.0007065113,0.002988967,0.002045899,0.0006572351,0.0009506168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000890943,"about_ca_system_score_gemma":0.0006283709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002815441,"about_ca_topic_score_gemma":0.004807279,"domain_scores_codex":[0.9972379,0.001465698,0.0002758763,0.0002800164,0.0004964921,0.0002440335],"domain_scores_gemma":[0.9773812,0.0146502,0.00427628,0.0007791298,0.002454582,0.0004585886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007509941,0.0001862909,0.5530797,0.002852753,0.0001214054,0.00138871,0.2781388,0.001052849,0.008513035,0.009007359,0.03009194,0.1148162],"study_design_scores_gemma":[0.00003001497,0.0002761204,0.551502,0.001414401,0.0001300609,0.0008348877,0.2478467,0.009817264,0.006206643,0.006568084,0.1751757,0.0001980367],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9673638,0.0004401072,0.00311364,0.0036903,0.000205872,0.0003125095,0.01085076,0.00009199327,0.01393109],"genre_scores_gemma":[0.9871001,0.0004527547,0.003569306,0.0009047054,0.0002164818,0.0004769875,0.004108917,0.00006257574,0.003108212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003411976,"threshold_uncertainty_score":0.01804447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1633074679594051,"score_gpt":0.3964180528346581,"score_spread":0.2331105848752531,"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."}}