{"id":"W4293087034","doi":"10.2196/38756","title":"COVID-19 Misinformation Detection: Machine-Learned Solutions to the Infodemic","year":2022,"lang":"en","type":"article","venue":"JMIR Infodemiology","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Texas at Austin","keywords":"Misinformation; Computer science; Credibility; Machine learning; Artificial intelligence; Set (abstract data type); Coronavirus disease 2019 (COVID-19); Data set; Information retrieval; Natural language processing; Computer security; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003279133,0.0001181212,0.0001570158,0.000215796,0.003812423,0.00006450306,0.0005629336,0.0001157204,0.002567779],"category_scores_gemma":[0.003657012,0.00009914524,0.00008685509,0.0007578129,0.0001739268,0.000406004,0.000332804,0.000486094,0.0004231558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007770592,"about_ca_system_score_gemma":0.0008633776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001880298,"about_ca_topic_score_gemma":0.002152763,"domain_scores_codex":[0.9977558,0.0007247838,0.0004738428,0.0001397635,0.0003922292,0.0005135303],"domain_scores_gemma":[0.9985062,0.0003847322,0.0002323965,0.0003153353,0.00007845632,0.0004828695],"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":[0.0002197152,0.00005603401,0.001590139,0.00002332261,0.00003325317,0.000001606612,0.3971201,0.1226268,0.00008473178,0.1557155,0.2832918,0.03923705],"study_design_scores_gemma":[0.0002689816,0.00008567063,0.002195648,9.750262e-7,0.000005152252,0.00002031725,0.01970689,0.004764994,0.000003072311,0.002099663,0.9707091,0.0001394704],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2800916,0.0002709889,0.06143695,0.3989508,0.003606066,0.004554816,0.0001877645,0.001472723,0.2494283],"genre_scores_gemma":[0.9368948,0.00003321223,0.0001222702,0.06123297,0.0001492991,0.0001856188,0.00003111091,0.00000619106,0.001344561],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6874174,"threshold_uncertainty_score":0.998344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09687160640888523,"score_gpt":0.3995396518257877,"score_spread":0.3026680454169025,"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."}}