{"id":"W2349209186","doi":"10.1016/j.nucengdes.2016.04.037","title":"An efficiency booster for energy conversion in natural circulation loops","year":2016,"lang":"en","type":"article","venue":"Nuclear Engineering and Design","topic":"Nuclear Engineering Thermal-Hydraulics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"University Network of Excellence in Nuclear Engineering; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Natural circulation; Booster (rocketry); Energy transformation; Efficient energy use; Nuclear engineering; Engineering; Materials science; Mechanical engineering; Environmental science; Aerospace engineering; Physics; Electrical engineering; Thermodynamics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001440346,0.0001756886,0.0001504806,0.0001648093,0.00002689805,0.0000336073,0.0001066673,0.0001059653,0.00001240511],"category_scores_gemma":[0.00002424357,0.0001559186,0.0000327953,0.0001061515,0.0000144023,0.0002346467,0.00001301592,0.00007786832,0.00001234792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008206703,"about_ca_system_score_gemma":0.000004161902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002730457,"about_ca_topic_score_gemma":5.316981e-7,"domain_scores_codex":[0.9992591,0.00001277264,0.0001587562,0.0001947785,0.0000872961,0.000287308],"domain_scores_gemma":[0.9996095,0.00009199523,0.00001304548,0.0001800174,0.00001776741,0.00008765297],"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":[0.0000352637,0.00001876481,0.00002962477,0.00008009436,0.0000167392,0.000005816643,0.0001961749,0.6105462,0.3757562,0.001536819,0.0002356327,0.01154259],"study_design_scores_gemma":[0.000646873,0.00006579341,0.001545007,0.0000652072,0.000006639171,0.00001053464,0.000008195464,0.988731,0.003425782,0.00004165855,0.005184148,0.0002692069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3578372,0.0003121822,0.6398558,0.00004781751,0.0005818813,0.0002210073,0.000004365075,0.001000821,0.0001389316],"genre_scores_gemma":[0.9940004,0.00003849672,0.005720401,0.0000303916,0.0000750689,0.000009419528,0.000002049399,0.0001049394,0.00001881389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6361632,"threshold_uncertainty_score":0.6358178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007220109985858986,"score_gpt":0.1770060616755139,"score_spread":0.1697859516896549,"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."}}