{"id":"W3127963587","doi":"10.21203/rs.3.rs-211261/v2","title":"When character forges the crisis: Personality traits of world leaders and differential policy responses to the COVID-19 pandemic","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Personality Traits and Psychology","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto General Hospital; University of Toronto; University Health Network","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Character (mathematics); Pandemic; Big Five personality traits; Character traits; Differential (mechanical device); Personality; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Psychology; Political science; Social psychology; Medicine; Virology; Internal medicine; Engineering; Mathematics; Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001188839,0.0001234318,0.0001297844,0.0004251522,0.0008247572,0.001977002,0.0001798273,0.0007692475,0.00278895],"category_scores_gemma":[0.008142643,0.000145308,0.0001158871,0.0003840138,0.0006305727,0.0008386325,0.0007260352,0.001736242,0.0003712865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003450837,"about_ca_system_score_gemma":0.0004609133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003640251,"about_ca_topic_score_gemma":0.006100771,"domain_scores_codex":[0.999432,0.000248079,0.00002022877,0.00004440166,0.00006600054,0.0001892189],"domain_scores_gemma":[0.9964612,0.0007665274,0.001167145,0.0001652434,0.0003353147,0.001104628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003838361,0.0002964735,0.9569887,0.00002273906,0.00008614116,0.0003007735,0.01770252,0.0002572325,0.001472679,0.001733896,0.002390193,0.01836472],"study_design_scores_gemma":[0.000005950864,0.00005850913,0.9798045,0.00001467958,0.000006989173,0.00007850411,0.01782467,0.0001890518,0.0001013191,0.0008767854,0.001027875,0.00001119562],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958759,0.00005290161,0.00005567284,0.001383489,0.00003769607,0.00000448609,0.00003204996,0.000001170658,0.002556575],"genre_scores_gemma":[0.9993659,0.00003828515,0.00002097743,0.0001594894,0.0000107086,0.000002703885,0.00001664015,0.00000166661,0.000383617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003640251,"threshold_uncertainty_score":0.009329975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3346502699410697,"score_gpt":0.5177471573279643,"score_spread":0.1830968873868946,"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."}}