{"id":"W4412931351","doi":"10.1016/j.pnucene.2025.105959","title":"Examining lessons learned from the COVID-19 response to inform nuclear emergency management","year":2025,"lang":"en","type":"article","venue":"Progress in Nuclear Energy","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Nuclear Laboratories","funders":"Atomic Energy of Canada Limited","keywords":"Emergency response; Coronavirus disease 2019 (COVID-19); Emergency management; Disaster response; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computer science; Nuclear engineering; Medical emergency; Medicine; Political science; Virology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01880311,0.000507123,0.0003327974,0.001566432,0.006074657,0.01000806,0.001600675,0.003177607,0.01135732],"category_scores_gemma":[0.045512,0.0002518021,0.0003545746,0.001783642,0.00582371,0.00736494,0.007622209,0.007539815,0.00145491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0132022,"about_ca_system_score_gemma":0.03068923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04284578,"about_ca_topic_score_gemma":0.1167386,"domain_scores_codex":[0.9916484,0.005565112,0.0002283663,0.0003614953,0.00107383,0.001122673],"domain_scores_gemma":[0.9723486,0.0173336,0.0009309706,0.001014566,0.005719763,0.002652444],"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":[0.0002550975,0.0007342875,0.03246737,0.001274486,0.00007053406,0.001664105,0.2528942,0.002930083,0.0007426006,0.1669643,0.1364008,0.4036022],"study_design_scores_gemma":[0.00003770153,0.0002815176,0.01790998,0.003532046,0.00005002894,0.0001597484,0.5615842,0.001565438,0.0009275744,0.04581972,0.3680505,0.00008153742],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2170889,0.005313172,0.007629895,0.5252189,0.003970241,0.0003706718,0.0007394347,0.0001538604,0.239515],"genre_scores_gemma":[0.9395679,0.006995181,0.008682428,0.02456819,0.0004729312,0.0002855899,0.0004961715,0.0001280005,0.01880369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04284578,"threshold_uncertainty_score":0.09944153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07448593964286143,"score_gpt":0.3695097865535297,"score_spread":0.2950238469106682,"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."}}