{"id":"W4205276384","doi":"10.2196/32378","title":"Charting the Information and Misinformation Landscape to Characterize Misinfodemics on Social Media: COVID-19 Infodemiology Study at a Planetary Scale","year":2021,"lang":"en","type":"article","venue":"JMIR Infodemiology","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Annenberg Foundation","keywords":"Misinformation; Social media; Internet privacy; Coronavirus disease 2019 (COVID-19); Narrative; Set (abstract data type); Social distance; Data science; Computer science; World Wide Web; Medicine; Computer security","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"],"consensus_categories":[],"category_scores_codex":[0.003151039,0.0002724536,0.0004888865,0.0002445829,0.001585954,0.0001573156,0.0003655272,0.0004394614,0.0003934875],"category_scores_gemma":[0.006477209,0.0002191278,0.0000824184,0.0004824208,0.0002874103,0.001053432,0.0003158709,0.0004796448,0.0003510843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003003204,"about_ca_system_score_gemma":0.000490947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002359359,"about_ca_topic_score_gemma":0.001735094,"domain_scores_codex":[0.9966561,0.0008169525,0.001122972,0.0002420777,0.0004727432,0.0006891838],"domain_scores_gemma":[0.9966607,0.001663076,0.000592401,0.0003222592,0.0002272833,0.0005342527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0005607411,0.00009266184,0.09652347,0.0000708998,0.00005188798,0.000006803545,0.8305206,0.0006936724,0.00004733203,0.006302078,0.04805324,0.01707658],"study_design_scores_gemma":[0.002115496,0.000228428,0.6199327,0.00001988946,0.00003703541,0.00006876263,0.1173332,0.001522072,0.00001413697,0.0005703069,0.2576196,0.000538332],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9655821,0.0000290059,0.0001783183,0.02362784,0.0004362415,0.001000382,0.00008267823,0.0001716656,0.008891739],"genre_scores_gemma":[0.9482297,0.0001142577,0.0001327437,0.05058731,0.0003632794,0.0000698385,0.0003849507,0.000009503438,0.0001084742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7131874,"threshold_uncertainty_score":0.9997138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08173063870867871,"score_gpt":0.3649928955162945,"score_spread":0.2832622568076158,"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."}}