{"id":"W2092231633","doi":"10.1016/j.anucene.2007.07.016","title":"A Raviart–Thomas–Schneider solution of the diffusion equation in hexagonal geometry","year":2007,"lang":"en","type":"article","venue":"Annals of Nuclear Energy","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hexagonal crystal system; Benchmark (surveying); Finite element method; Geometry; Diffusion; Mathematics; Core (optical fiber); Set (abstract data type); Polynomial; Matrix (chemical analysis); Applied mathematics; Mathematical analysis; Computer science; Physics; Materials science; Thermodynamics; Chemistry","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":[0.000366533,0.00008209347,0.0001543024,0.000125521,0.00002226752,0.000002826865,0.0001311688,0.00006599913,0.00002093559],"category_scores_gemma":[0.0002531652,0.00006956454,0.00006801286,0.0004244026,0.00005020384,0.00007261946,0.00005504987,0.00008749186,0.00000172238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002026668,"about_ca_system_score_gemma":0.000006849147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001826484,"about_ca_topic_score_gemma":0.000005785206,"domain_scores_codex":[0.9991247,0.00004003257,0.0003609526,0.00008260803,0.0002414458,0.0001502736],"domain_scores_gemma":[0.9992939,0.000349121,0.0001041061,0.0001504661,0.00007409049,0.00002829643],"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":[0.00009560361,0.0003397118,0.0006521615,0.0002450193,0.00005805314,0.000003324954,0.0006477944,0.4064239,0.1270449,0.2431494,0.0008180644,0.2205221],"study_design_scores_gemma":[0.0005282015,0.0001320175,0.06526373,0.0003182866,0.00001423282,0.000008582087,0.0001764624,0.6038892,0.06203463,0.2560834,0.01119155,0.000359726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.382975,0.0001842099,0.6139507,0.0002077854,0.000216534,0.0000577094,0.000002980052,0.00004731469,0.002357787],"genre_scores_gemma":[0.9403757,0.00004345683,0.05937796,0.0001237179,0.00003491921,0.000001075408,0.000001386201,0.00002250667,0.0000192344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5574008,"threshold_uncertainty_score":0.2836759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05731757850078029,"score_gpt":0.3151353789091615,"score_spread":0.2578178004083812,"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."}}