{"id":"W4232295146","doi":"10.1016/j.jnucmat.2010.01.006","title":"A general model for predicting coolant activity behaviour for fuel-failure monitoring analysis","year":2010,"lang":"en","type":"article","venue":"Journal of Nuclear Materials","topic":"Nuclear Materials and Properties","field":"Materials Science","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bruce Power (Canada); Autodesk (Canada); Royal Military College of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Atomic Energy of Canada Limited; Bruce Power","keywords":"Nuclear engineering; Coolant; Burnup; Nuclear fission product; Fuel element failure; Shutdown; Nuclear reactor core; Natural uranium; Fission products; Bundle; Decay heat; Environmental science; Uranium; Materials science; Engineering; Mechanical engineering","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":[0.0006567924,0.000831142,0.001250989,0.0006172666,0.0005553314,0.0007910384,0.001868004,0.001790302,0.003554736],"category_scores_gemma":[0.002018075,0.0007167076,0.001261472,0.0006466025,0.0005096598,0.001455785,0.0006735438,0.001072482,0.001050899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009056022,"about_ca_system_score_gemma":0.001091015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01768391,"about_ca_topic_score_gemma":0.01139413,"domain_scores_codex":[0.9998317,0.00003127717,0.000009837931,0.00005245709,0.00004344936,0.00003119174],"domain_scores_gemma":[0.9995005,0.0002517046,0.00004231142,0.0000506958,0.0001310985,0.00002376144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001115137,0.00001141089,0.0002223136,0.0000177572,0.00001061924,0.00002222134,0.00000870534,0.9934823,0.0009553555,0.00122013,0.0002408983,0.003797169],"study_design_scores_gemma":[0.000001168922,0.000002827714,0.00004547164,7.598663e-7,0.000002526796,0.000003342529,7.395035e-7,0.9993203,0.00008965889,0.0004537363,0.00007779722,0.000001668946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03493397,0.0003519565,0.9600793,0.0001912706,0.00005948182,0.00007784766,0.0004223903,0.001098574,0.002785224],"genre_scores_gemma":[0.8562096,0.0007948093,0.1226809,0.0001614728,0.0001152326,0.0004224073,0.0009846882,0.0005816036,0.01804925],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01768391,"threshold_uncertainty_score":0.03516197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02907926322924662,"score_gpt":0.2763885077752474,"score_spread":0.2473092445460008,"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."}}