{"id":"W4226187513","doi":"10.1186/s12889-022-13151-7","title":"From science to politics: COVID-19 information fatigue on YouTube","year":2022,"lang":"en","type":"article","venue":"BMC Public Health","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Toronto; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Pandemic; Public health; Social media; Politics; Biostatistics; Coronavirus disease 2019 (COVID-19); Audience measurement; Entertainment; Medicine; Masking (illustration); Public relations; Advertising; Political science; Nursing; Business","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005203361,0.00007667257,0.0001111368,0.0005203656,0.003443379,0.000506975,0.0005630865,0.00002650122,0.001810132],"category_scores_gemma":[0.00614687,0.0000771081,0.00002764098,0.001450015,0.0001505879,0.001975963,0.0001307795,0.0001504296,0.0002922848],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003005714,"about_ca_system_score_gemma":0.01906806,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02607171,"about_ca_topic_score_gemma":0.0007572087,"domain_scores_codex":[0.9970224,0.0003221452,0.0003676521,0.0001395901,0.001444462,0.0007037239],"domain_scores_gemma":[0.9973003,0.0001582107,0.000172263,0.000256924,0.0001228121,0.001989525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007363369,0.00005205079,0.0005206013,0.00001662154,0.00000174377,1.367659e-7,0.4905773,0.0004748249,7.343958e-7,0.3960305,0.0969165,0.01540159],"study_design_scores_gemma":[0.0002154688,0.0001080909,0.003851618,0.000002467859,3.693788e-7,4.06017e-7,0.108669,0.0003201094,0.000001395049,0.0007179823,0.8860221,0.00009100761],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2965334,0.00002066104,0.02871064,0.3744726,0.002361497,0.001798783,0.0007293088,0.0005875115,0.2947855],"genre_scores_gemma":[0.8790297,0.000005264803,0.0007148526,0.1194675,0.0001900519,0.00001570035,0.00008305004,0.000003774192,0.0004900547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7891056,"threshold_uncertainty_score":0.9991024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1641604237377347,"score_gpt":0.4306128178955823,"score_spread":0.2664523941578476,"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."}}