{"id":"W4280589992","doi":"10.2196/30167","title":"Themes Surrounding COVID-19 and Its Infodemic: Qualitative Analysis of the COVID-19 Discussion on the Multidisciplinary Healthcare Information for All Health Forum","year":2022,"lang":"en","type":"article","venue":"JMIR Infodemiology","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health; Institute of Health Services and Policy Research","funders":"","keywords":"Misinformation; Thematic analysis; Health care; Pandemic; Public relations; Qualitative research; Multidisciplinary approach; Political science; Timeline; Focus group; Health literacy; Psychology; Coronavirus disease 2019 (COVID-19); Medicine; Sociology; Geography; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02232264,0.0008480193,0.0009216202,0.002825401,0.01167701,0.005656549,0.001883902,0.002584854,0.003762015],"category_scores_gemma":[0.03560614,0.0005997842,0.000558233,0.002452701,0.01261357,0.006362901,0.009644417,0.003830632,0.000427681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007329253,"about_ca_system_score_gemma":0.005510964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006214757,"about_ca_topic_score_gemma":0.007197688,"domain_scores_codex":[0.9825569,0.0135266,0.000404065,0.0006954169,0.001148974,0.001668117],"domain_scores_gemma":[0.9400641,0.05065019,0.002398047,0.0006865761,0.002923664,0.003277363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002905525,0.00001650927,0.001092801,0.0001283589,0.000001680071,0.0002958992,0.9949834,0.00001697467,0.0003049225,0.001045757,0.0004935337,0.001591065],"study_design_scores_gemma":[0.000003640883,0.00002113976,0.0008322691,0.0001731052,0.000002274369,0.00007068737,0.9924269,0.00005637306,0.0001978331,0.0002252371,0.005982,0.000008727488],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793378,0.0006690586,0.003825098,0.006127858,0.0003133832,0.0005070838,0.0005195678,0.0000385284,0.008661606],"genre_scores_gemma":[0.9900984,0.0006491406,0.001817927,0.001575903,0.0001239426,0.0009518744,0.000198233,0.00007984608,0.004504745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02232264,"threshold_uncertainty_score":0.1180548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1976025037708518,"score_gpt":0.5195063459330506,"score_spread":0.3219038421621988,"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."}}