{"id":"W4376618583","doi":"10.1101/2023.05.10.23289764","title":"Ability to detect fake news predicts sub-national variation in COVID-19 vaccine uptake across the UK","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Economic and Social Research Council; Engineering and Physical Sciences Research Council; Cambridge Trust","keywords":"Misinformation; Coronavirus disease 2019 (COVID-19); Perspective (graphical); Psychological intervention; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Psychology; Sample (material); Government (linguistics); Scale (ratio); Social psychology; Medicine; Geography; Computer science; Virology; Psychiatry; Disease; Outbreak; Cartography; Computer security","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002097234,0.0001987504,0.0002718966,0.0009406077,0.0003385446,0.001283985,0.0003336335,0.0005731597,0.00391949],"category_scores_gemma":[0.02330294,0.0002104069,0.0003512866,0.0008678135,0.0008626575,0.0007342562,0.00127299,0.0006653978,0.0005623131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005877399,"about_ca_system_score_gemma":0.0003783352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03062927,"about_ca_topic_score_gemma":0.01918134,"domain_scores_codex":[0.9986258,0.0005883668,0.0001455666,0.0002718214,0.0002111731,0.0001572456],"domain_scores_gemma":[0.9744464,0.01132858,0.008265059,0.002813463,0.001938031,0.001208557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006629946,0.00002827506,0.9960839,0.00001067221,0.00005360529,0.00003999957,0.0008977219,0.0001891822,0.0001509899,0.00007999293,0.0001679937,0.002231396],"study_design_scores_gemma":[0.000001489203,0.00003240253,0.9987139,0.000006856969,0.000008964623,0.00002414429,0.0005955623,0.0003724075,0.00006334325,0.00005485756,0.000122039,0.000004181838],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987583,0.00003464094,0.0001474296,0.000120844,0.000004055252,0.000005110596,0.0002236473,0.000002398074,0.0007035275],"genre_scores_gemma":[0.9995577,0.00002531696,0.00005816605,0.00001275109,0.000001773087,0.00000370159,0.000120675,0.00000170293,0.0002181318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03062927,"threshold_uncertainty_score":0.060902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08189744218443169,"score_gpt":0.3849976111908942,"score_spread":0.3031001690064625,"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."}}