{"id":"W4396593947","doi":"10.2139/ssrn.4813710","title":"Examining Lessons Learned from the Covid-19 Response to Inform Nuclear Emergency Management","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Nuclear Laboratories; Atomic Energy (Canada)","funders":"","keywords":"Emergency response; Coronavirus disease 2019 (COVID-19); Emergency management; Disaster response; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Business; Political science; Psychology; Medical emergency; Medicine; Virology; Pathology; Law; Outbreak","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":[0.01674569,0.0004042953,0.0002773098,0.0009674605,0.005180607,0.009203855,0.001671038,0.003223622,0.01187868],"category_scores_gemma":[0.04481092,0.0002285228,0.0002862176,0.001362491,0.006715298,0.00694058,0.006221431,0.005973565,0.001508254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01008114,"about_ca_system_score_gemma":0.0133809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03032424,"about_ca_topic_score_gemma":0.06404933,"domain_scores_codex":[0.9921532,0.005746836,0.0001336945,0.0003328061,0.0008399148,0.0007935764],"domain_scores_gemma":[0.976335,0.01674671,0.0007276594,0.001230871,0.003489641,0.00147009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003631572,0.0007548843,0.0304809,0.0009376364,0.00008441375,0.002424073,0.2888215,0.005357075,0.001141571,0.2268536,0.1019188,0.3408625],"study_design_scores_gemma":[0.00006104165,0.0003930404,0.01818492,0.001896628,0.00004794765,0.0002677025,0.5632927,0.003753279,0.001488903,0.07949435,0.3310346,0.00008485865],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3975144,0.002981057,0.008624109,0.3433049,0.002359811,0.0002913871,0.0005015101,0.0001529438,0.24427],"genre_scores_gemma":[0.9702253,0.002062223,0.004152739,0.01019465,0.0002267791,0.0001105513,0.0001890296,0.0001050237,0.01273372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03032424,"threshold_uncertainty_score":0.0885607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08255023654896392,"score_gpt":0.3696841724317688,"score_spread":0.2871339358828049,"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."}}