{"id":"W2915204566","doi":"10.1299/jsmeicone.2015.23._icone23-1_104","title":"ICONE23-1198 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; Europium; Enriched uranium; Uranium oxide; Neutron poison; Materials science; Neutron capture; Neutron; Environmental science; Neutron temperature; Uranium; 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":[0.000412236,0.000310004,0.0004540304,0.0002669496,0.0004482129,0.0003580854,0.0005371729,0.0003763633,0.002169485],"category_scores_gemma":[0.0004405147,0.0001107363,0.0002152295,0.0003156117,0.0002283425,0.0004527764,0.0001612337,0.0003908428,0.0002271763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007455755,"about_ca_system_score_gemma":0.0004356686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004989929,"about_ca_topic_score_gemma":0.008329337,"domain_scores_codex":[0.9998989,0.00001283202,0.000003799915,0.00001550876,0.00004605334,0.00002289951],"domain_scores_gemma":[0.9997663,0.00008447417,0.00002248434,0.00002287543,0.00007861081,0.00002523358],"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":[0.004604705,0.0006822919,0.01370402,0.0004200369,0.00007371635,0.001141891,0.0003517974,0.3608165,0.5752589,0.002705358,0.002458018,0.03778284],"study_design_scores_gemma":[0.0001711427,0.002863415,0.008143897,0.00002127823,0.00003946976,0.0001393117,0.0002025209,0.2874655,0.6960795,0.0002830892,0.004553197,0.0000377408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954101,0.00009443551,0.001442229,0.00004195621,0.00001116391,0.00001397897,0.0001387063,0.00007740773,0.002769908],"genre_scores_gemma":[0.9975783,0.00004711704,0.001041712,0.00001194962,0.000001046863,0.000006564235,0.0001185998,0.0000255792,0.001169121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004989929,"threshold_uncertainty_score":0.00992173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04331230933477558,"score_gpt":0.2499272162965177,"score_spread":0.2066149069617421,"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."}}