{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004278765,0.0003083345,0.000454028,0.0002756371,0.0004374845,0.0003634094,0.0005377044,0.0003730146,0.002180545],"category_scores_gemma":[0.000451872,0.0001102796,0.0002170478,0.0003136446,0.0002287499,0.0004535046,0.0001635473,0.0003853302,0.0002206423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007596134,"about_ca_system_score_gemma":0.000453566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004816826,"about_ca_topic_score_gemma":0.007974425,"domain_scores_codex":[0.9998978,0.00001320783,0.00000380603,0.00001523527,0.00004703866,0.00002281639],"domain_scores_gemma":[0.9997646,0.00008609668,0.00002272762,0.00002306158,0.00007832273,0.00002521143],"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":[0.004418678,0.0007076924,0.01359217,0.0004197824,0.00007430014,0.001056469,0.0003246883,0.3961547,0.5384865,0.002865246,0.002531082,0.03936862],"study_design_scores_gemma":[0.0001724558,0.002853105,0.00790675,0.00002119149,0.00004073739,0.0001346137,0.0001881464,0.3216273,0.6620718,0.0002921816,0.004654543,0.00003727148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949294,0.000101038,0.0017093,0.00004597547,0.00001248455,0.00001487865,0.0001424166,0.00008605149,0.002958484],"genre_scores_gemma":[0.9974194,0.00004825026,0.001184845,0.00001232271,0.000001125823,0.00000660308,0.0001222554,0.00002646646,0.001178788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004816826,"threshold_uncertainty_score":0.009577572,"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."}}