{"id":"W4377263763","doi":"10.1016/j.nucengdes.2023.112380","title":"OECD/NEA R&D priorities for loss-of-cooling and loss-of-coolant accidents in Spent-Fuel-Pools","year":2023,"lang":"en","type":"article","venue":"Nuclear Engineering and Design","topic":"Nuclear Materials and Properties","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Nuclear Safety Commission; Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas; Japan Atomic Energy Agency; Institut de Radioprotection et de SÛreté Nucléaire; Korea Atomic Energy Research Institute; European Commission","keywords":"Coolant; Engineering; Loss-of-coolant accident; Nuclear power; Nuclear engineering; Environmental science; Forensic engineering; Waste management; Mechanical engineering; Nuclear physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005766629,0.0001443007,0.0003153803,0.0001343815,0.00004473105,0.00009506767,0.0001250477,0.00007744307,0.00007453556],"category_scores_gemma":[0.0001091771,0.0001309158,0.00003080485,0.00008030422,0.00006306093,0.0001662364,0.00009032528,0.00005491183,0.00003911371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001234428,"about_ca_system_score_gemma":0.00001478617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007064926,"about_ca_topic_score_gemma":0.000002184202,"domain_scores_codex":[0.9990494,0.00003055537,0.0003104229,0.0002116089,0.0001309352,0.000267103],"domain_scores_gemma":[0.9995484,0.0001484896,0.00006874483,0.0001464615,0.00003169436,0.0000561904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003626882,0.00001843655,0.0008754489,0.001089286,0.00001546969,0.00001138169,0.001971311,0.003772117,0.9896097,0.001020672,0.0001894131,0.001064083],"study_design_scores_gemma":[0.006928205,0.001742358,0.09537175,0.003162057,0.0001862664,0.0001861896,0.001479527,0.06634417,0.7812872,0.004769206,0.0358519,0.002691158],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981655,0.0003901986,0.0007374801,0.00002809956,0.0002982732,0.0002416169,0.00002339516,0.00009744085,0.00001801696],"genre_scores_gemma":[0.9921191,0.0003806279,0.007300533,0.00001193948,0.00005969848,0.000009061288,0.000002005447,0.00004414388,0.00007287039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2083225,"threshold_uncertainty_score":0.5338592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04363283649329817,"score_gpt":0.2544562422600368,"score_spread":0.2108234057667386,"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."}}