{"id":"W4386837229","doi":"10.3390/geographies3030031","title":"Temporal Relationship between Daily Reports of COVID-19 Infections and Related GDELT and Tweet Mentions","year":2023,"lang":"en","type":"article","venue":"Geographies","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Social media; Globe; Geography; Anomaly (physics); History; Political science; Demography; Disease; Medicine; Sociology; Infectious disease (medical specialty)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009360563,0.0001616521,0.0002021266,0.002259338,0.0001773355,0.000928204,0.0002351531,0.0002903294,0.002205675],"category_scores_gemma":[0.008111493,0.0001130855,0.0001982957,0.002416119,0.0002230533,0.0009322322,0.0007384226,0.0004972777,0.0006079137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000253394,"about_ca_system_score_gemma":0.0001947491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005672662,"about_ca_topic_score_gemma":0.008813779,"domain_scores_codex":[0.999342,0.0001199315,0.0001064937,0.0001365131,0.0001952376,0.00009970913],"domain_scores_gemma":[0.9871851,0.004925441,0.006039659,0.0003407522,0.001082355,0.0004268142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001473664,0.00003435649,0.9820932,0.000146653,0.00008973411,0.0002396637,0.001128036,0.0007298063,0.0009166794,0.0004658371,0.002273059,0.01173573],"study_design_scores_gemma":[0.000003261143,0.00006196047,0.990921,0.00004097173,0.00003206763,0.0002282723,0.001880863,0.001778801,0.0006233885,0.0001395309,0.004272223,0.0000178084],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832675,0.0002904697,0.0005004017,0.000234441,0.00003063356,0.00002423998,0.01226455,0.00005887601,0.003329026],"genre_scores_gemma":[0.9871628,0.0002495287,0.0006550399,0.00003714842,0.00005597061,0.00003690126,0.0106339,0.00001582223,0.001152952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005672662,"threshold_uncertainty_score":0.01127928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0556555772685971,"score_gpt":0.3510990687297631,"score_spread":0.295443491461166,"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."}}