{"id":"W3206867380","doi":"10.1128/spectrum.00683-21","title":"Generation of False-Positive SARS-CoV-2 Antigen Results with Testing Conditions outside Manufacturer Recommendations: A Scientific Approach to Pandemic Misinformation","year":2021,"lang":"en","type":"article","venue":"Microbiology Spectrum","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Pandemic; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Misinformation; Coronavirus disease 2019 (COVID-19); False positive paradox; 2019-20 coronavirus outbreak; Coronavirus; Virology; Medicine; Severe acute respiratory syndrome coronavirus; Computer science; Internal medicine; Outbreak; Artificial intelligence; Computer security; Disease","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003810347,0.0001808121,0.0003009661,0.0003380176,0.0003039962,0.00005792889,0.00007151315,0.000136419,0.000007974346],"category_scores_gemma":[0.0004521584,0.0001595536,0.0000605799,0.0007612476,0.0001468752,0.0001347948,0.00004208038,0.0002263745,0.00005052781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001289311,"about_ca_system_score_gemma":0.0002116953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006848198,"about_ca_topic_score_gemma":0.0002332516,"domain_scores_codex":[0.9985573,0.0001062807,0.0005186196,0.0004476346,0.00008320765,0.0002869778],"domain_scores_gemma":[0.9988801,0.0001334687,0.0002587377,0.0003181111,0.0003762663,0.00003326435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000723229,0.0001133437,0.001626896,0.00002038366,0.00007148406,0.000006546894,0.0006768063,0.00003482369,0.9947119,0.00004865926,0.002085914,0.0005308547],"study_design_scores_gemma":[0.001186987,0.000196676,0.003213621,0.0001310525,0.00006060481,0.001357913,0.0002838307,0.0005952354,0.9900593,0.00005153845,0.002693204,0.0001700689],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865344,0.0000536868,0.007747144,0.001063403,0.000259603,0.0005055544,0.0002074825,0.0001224176,0.003506274],"genre_scores_gemma":[0.973815,0.000002067954,0.02207948,0.001860639,0.00009793296,0.00002286317,0.001956158,0.00001852439,0.0001473721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01433233,"threshold_uncertainty_score":0.6506406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09944371753125417,"score_gpt":0.3193418134237745,"score_spread":0.2198980958925203,"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."}}