{"id":"W2633676823","doi":"10.1299/jsmeicone.2015.23._icone23-1_101","title":"ICONE23-1189 FUELLING STUDY USING BURNABLE NEUTRON ABSORBERS: MITIGATING FUELLING TRANSIENTS AND IMPROVING POWER COMPLIANCE MARGIN DURING REFUELLING","year":2015,"lang":"en","type":"article","venue":"The Proceedings of the International Conference on Nuclear Engineering (ICONE)","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Nuclear engineering; Enriched uranium; Uranium oxide; Neutron poison; Europium; Neutron capture; Materials science; Environmental science; Neutron; Uranium; Neutron temperature; Nuclear physics; Engineering; Physics; Metallurgy","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":[],"consensus_categories":[],"category_scores_codex":[0.0002831389,0.0002278677,0.0002145173,0.00006742003,0.0002699345,0.0002675972,0.0006149751,0.00003250099,0.00003908006],"category_scores_gemma":[0.00001410154,0.0001822477,0.0000850325,0.0001584607,0.00006345642,0.000271638,0.0001949018,0.0004292069,0.000007434676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006585226,"about_ca_system_score_gemma":0.00002208263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001613147,"about_ca_topic_score_gemma":3.931854e-7,"domain_scores_codex":[0.9987075,0.000008038262,0.0003418715,0.000314194,0.0003636442,0.0002647615],"domain_scores_gemma":[0.9991633,0.00003054333,0.0002762835,0.0001511386,0.0002907014,0.00008805612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009409575,0.0002989907,0.004449333,0.0001082976,0.0002825739,7.1723e-7,0.006512168,0.0317418,0.7842034,0.1715811,0.00001372267,0.0007138698],"study_design_scores_gemma":[0.002187201,0.0002000496,0.005217672,0.001211787,0.0001580814,0.00001299505,0.02235442,0.9339598,0.02547055,0.008146482,0.0002271011,0.0008539042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995747,0.00001653059,0.0002054678,0.0002640142,0.0001914502,0.0003278026,0.000008500509,0.00005026589,0.003188955],"genre_scores_gemma":[0.9988961,0.000003551934,0.0007471293,0.00001675112,0.0001740388,0.00001028571,9.566022e-7,0.00005387151,0.00009732539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.902218,"threshold_uncertainty_score":0.7431844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04603378903776865,"score_gpt":0.2524861905495391,"score_spread":0.2064524015117704,"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."}}