{"id":"W4285028795","doi":"10.2196/34231","title":"The Role of Influential Actors in Fostering the Polarized COVID-19 Vaccine Discourse on Twitter: Mixed Methods of Machine Learning and Inductive Coding","year":2022,"lang":"en","type":"article","venue":"JMIR Infodemiology","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Florida Center for Cybersecurity, University of South Florida","keywords":"Disinformation; Influencer marketing; Social media; Population; Public relations; Political science; Sociology; Business","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":[0.003235281,0.00009925597,0.0002990853,0.0001048228,0.0006848038,0.00001221367,0.0002968916,0.00007324468,0.0000611125],"category_scores_gemma":[0.001599927,0.00006572935,0.00006165082,0.0002505198,0.00008558544,0.00007708235,0.0005291632,0.0005451344,2.195442e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001023624,"about_ca_system_score_gemma":0.0001289196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002913859,"about_ca_topic_score_gemma":0.001302716,"domain_scores_codex":[0.9963592,0.002701345,0.0003858273,0.0001680234,0.000137349,0.0002482285],"domain_scores_gemma":[0.9969501,0.00247847,0.000352836,0.0001396271,0.0000257298,0.00005325882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005918437,0.00004562879,0.8910568,0.00001382042,0.00004743528,0.000002116991,0.05986294,0.0005669082,0.01538993,0.01756323,0.00003371589,0.01482564],"study_design_scores_gemma":[0.004804748,0.001333266,0.6561986,0.0000507431,0.00009861548,0.0000142046,0.2047798,0.003047777,0.00199106,0.05182345,0.07527173,0.0005860158],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952021,0.0004934408,0.000250036,0.003077661,0.0001555226,0.0003354993,0.00000519235,0.00001408451,0.0004665044],"genre_scores_gemma":[0.9992331,0.0001153088,0.0001518827,0.0003432151,0.00004768487,0.00006469449,0.000002375052,0.000006890469,0.00003488071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2348582,"threshold_uncertainty_score":0.5267026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04569616509931237,"score_gpt":0.421187638836937,"score_spread":0.3754914737376246,"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."}}