{"id":"W4402070853","doi":"10.2196/53127","title":"Tracking the denial related to protective measures during the COVID-19 pandemic: the case of #AglomeraBrasil on Twitter (Preprint)","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Preprint; Coronavirus disease 2019 (COVID-19); Pandemic; Denial; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Tracking (education); Virology; Psychology; Computer science; Medicine; World Wide Web; Psychoanalysis; Infectious disease (medical specialty); Pathology; Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004873019,0.0002711673,0.0002470455,0.001233417,0.006328364,0.003032971,0.001237034,0.004973118,0.008547175],"category_scores_gemma":[0.03408054,0.0003008621,0.0002736084,0.001119169,0.001798184,0.004447727,0.003336319,0.005058858,0.001599972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00251344,"about_ca_system_score_gemma":0.00221643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03887403,"about_ca_topic_score_gemma":0.03320254,"domain_scores_codex":[0.9971182,0.001458424,0.0001628652,0.0002689447,0.0004706274,0.0005209832],"domain_scores_gemma":[0.973813,0.01558597,0.004890916,0.001632312,0.001856749,0.002221121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00132802,0.0006341832,0.3897474,0.0006108045,0.0001561808,0.01137929,0.2581593,0.002058622,0.006477968,0.0298364,0.1324098,0.167202],"study_design_scores_gemma":[0.0001090568,0.0007328136,0.2045542,0.0009846903,0.0001781739,0.00429443,0.4514228,0.01638096,0.004640508,0.01642644,0.2999343,0.000341607],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.817951,0.0004160831,0.002502778,0.1270312,0.0008138763,0.0001333394,0.00143985,0.000233887,0.04947809],"genre_scores_gemma":[0.9835439,0.0003067988,0.001553611,0.007674259,0.0002820843,0.00005904547,0.0003835938,0.00005854264,0.006138204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03887403,"threshold_uncertainty_score":0.07729554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2303399879759555,"score_gpt":0.499768653892089,"score_spread":0.2694286659161335,"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."}}