{"id":"W4205376890","doi":"10.2196/preprints.32452","title":"COVID-19 and Vitamin D Misinformation on YouTube: Content Analysis (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Simon Fraser University; University of British Columbia; University of Alberta; World Wildlife Fund Canada; Alberta Health Services","funders":"Alberta Innovates; Ministero dello Sviluppo Economico; Government of Alberta","keywords":"Misinformation; Content analysis; Social media; Coronavirus disease 2019 (COVID-19); Psychology; Pandemic; Medicine; Internet privacy; Computer science; World Wide Web; Sociology; Disease; Pathology; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002023936,0.0002421562,0.0002656552,0.005280843,0.0009084378,0.001903976,0.0002537375,0.0003753507,0.01161913],"category_scores_gemma":[0.01642017,0.0001250257,0.0003822132,0.006786255,0.0005784263,0.001649339,0.001154347,0.000430282,0.001808161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002113907,"about_ca_system_score_gemma":0.001555883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0146158,"about_ca_topic_score_gemma":0.01710229,"domain_scores_codex":[0.9988769,0.0003872491,0.0001438684,0.0001336358,0.0003308553,0.0001274802],"domain_scores_gemma":[0.9829211,0.01173219,0.001745822,0.0002681707,0.003046975,0.0002858948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0008305268,0.000447477,0.3496889,0.01021534,0.0002192988,0.001060086,0.184796,0.0003903813,0.00371317,0.004095277,0.1844149,0.2601287],"study_design_scores_gemma":[0.00003533545,0.0002026693,0.7207402,0.002904059,0.0001182457,0.0002666445,0.187277,0.001683684,0.001477709,0.0006992554,0.08451473,0.00008042921],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8993866,0.001672037,0.001630943,0.004383857,0.0003211605,0.003047289,0.07165823,0.000166191,0.01773376],"genre_scores_gemma":[0.9086733,0.004594106,0.01008777,0.001603351,0.0006374876,0.008929826,0.04559806,0.0002449109,0.01963116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0146158,"threshold_uncertainty_score":0.03886986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1092044014204402,"score_gpt":0.3660746003761841,"score_spread":0.2568701989557439,"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."}}