{"id":"W4413552068","doi":"10.64628/aam.fddqs6kgd","title":"#COVID19: Social media both a blessing and a curse during coronavirus pandemic","year":2020,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Blessing; Pandemic; Curse; Coronavirus; Coronavirus disease 2019 (COVID-19); Virology; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Political science; Sociology; Medicine; Geography; Infectious disease (medical specialty); Anthropology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005316166,0.0004884771,0.001146699,0.0003283546,0.0002320025,0.0003035297,0.0004367686,0.0006381337,0.0005137799],"category_scores_gemma":[0.001088698,0.0006010579,0.0002303621,0.0001848978,0.0001775972,0.0002055975,0.00127015,0.001135031,0.0002462617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005637902,"about_ca_system_score_gemma":0.0003319488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009408243,"about_ca_topic_score_gemma":0.0002096812,"domain_scores_codex":[0.9970996,0.00003404144,0.0009820176,0.001189287,0.0000892251,0.0006058086],"domain_scores_gemma":[0.9981639,0.0002616067,0.0007432544,0.0004087187,0.00002272623,0.0003997443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004496617,0.0002952885,0.8438352,0.004056212,0.001071437,0.0002380254,0.04525109,0.0003454727,0.0009677142,0.0725874,0.007653719,0.02324882],"study_design_scores_gemma":[0.006673128,0.00007290907,0.6522942,0.0005386822,0.0001934372,0.00007304404,0.0009636471,0.009625619,0.0001370379,0.27089,0.05432017,0.004218189],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717988,0.007530784,0.003346831,0.004189047,0.001617597,0.0006451957,0.0007404037,0.0005234198,0.00960795],"genre_scores_gemma":[0.9947696,0.001334119,0.0005744122,0.001931999,0.0008692755,0.00004188108,0.00005478229,0.00009364563,0.0003302847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1983026,"threshold_uncertainty_score":0.9996441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1573504597237217,"score_gpt":0.3147396307900304,"score_spread":0.1573891710663087,"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."}}