{"id":"W3209529918","doi":"10.5539/cis.v14n4p57","title":"Automatic Identification and Filtration of COVID-19 Misinformation","year":2021,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Misinformation; Disinformation; Computer science; Social media; Identification (biology); Coronavirus disease 2019 (COVID-19); Pandemic; Fake news; Internet privacy; Artificial intelligence; Data science; Computer security; World Wide Web; Medicine","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":[0.001372718,0.00102924,0.0006223544,0.005954393,0.0008177442,0.001339694,0.0006519135,0.001160691,0.001069448],"category_scores_gemma":[0.006558686,0.0002728598,0.0005759518,0.001550321,0.0004794307,0.001863366,0.001094825,0.001207212,0.001500198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009103406,"about_ca_system_score_gemma":0.001414134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005829229,"about_ca_topic_score_gemma":0.009135478,"domain_scores_codex":[0.9986522,0.0001835233,0.0001808754,0.0003118745,0.0004736111,0.0001980507],"domain_scores_gemma":[0.9953998,0.001666953,0.0009265125,0.0003976274,0.001470656,0.0001384467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001900557,0.0006580627,0.07504473,0.001271887,0.0002663237,0.003484189,0.001759029,0.01510029,0.09487303,0.004213861,0.03588606,0.7655421],"study_design_scores_gemma":[0.0000409706,0.0005866635,0.06189855,0.0002821579,0.0002448895,0.002050112,0.001488834,0.7854816,0.1108943,0.005087306,0.03182074,0.0001238672],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8024297,0.003355779,0.1614843,0.001975458,0.00112951,0.000703101,0.01007421,0.006583854,0.01226412],"genre_scores_gemma":[0.8895515,0.001023913,0.08615554,0.0002548224,0.0004595561,0.0001349904,0.01532645,0.0001371287,0.006956095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005954393,"threshold_uncertainty_score":0.0115906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03135108471246531,"score_gpt":0.3356997377740543,"score_spread":0.304348653061589,"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."}}