{"id":"W3162564821","doi":"10.2196/23105","title":"Using Machine Learning to Compare Provaccine and Antivaccine Discourse Among the Public on Social Media: Algorithm Development Study","year":2021,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"College of Engineering, Michigan State University; Michigan State University","keywords":"Persuasion; Social media; Framing (construction); Content analysis; Public engagement; Public discourse; Computer science; User engagement; Sociology; Public relations; Artificial intelligence; Psychology; Social psychology; Political science; World Wide Web; Social science; Politics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002128698,0.0002065815,0.0004444999,0.0001231967,0.002795447,0.000431059,0.0001904858,0.00004903371,0.0000535059],"category_scores_gemma":[0.0007621422,0.0001569652,0.00003136754,0.0007937024,0.00003966096,0.0002749288,0.0001758777,0.0003611413,0.000003649005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001183969,"about_ca_system_score_gemma":0.001321937,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004572914,"about_ca_topic_score_gemma":0.03228047,"domain_scores_codex":[0.9967618,0.00107874,0.0004105596,0.0004798441,0.000501919,0.0007671448],"domain_scores_gemma":[0.9984941,0.0002891049,0.0001598352,0.0001694797,0.0002568015,0.0006306175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001291054,0.0001961991,0.8560644,0.00002495369,0.00002578385,0.00001990703,0.03933385,6.666565e-7,0.000001348902,0.0003076218,0.00071241,0.1033],"study_design_scores_gemma":[0.0008383672,0.00007165438,0.9001131,0.00001419653,0.00000115961,0.000005081561,0.03459652,0.0002155881,5.846734e-7,0.00001513104,0.06391799,0.0002106514],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.944649,0.001250973,0.0001664255,0.05265801,0.0001939581,0.0008136908,0.000009152188,0.00007238627,0.0001863475],"genre_scores_gemma":[0.9976529,0.0002116129,0.0002865559,0.001056615,0.0004773932,0.00005738412,0.00003324348,0.00001944236,0.0002047932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1030893,"threshold_uncertainty_score":0.9985028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08014349250463887,"score_gpt":0.3741185174688575,"score_spread":0.2939750249642186,"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."}}