{"id":"W4415069994","doi":"10.1016/j.nexres.2025.100885","title":"The finite element neural network method: One-dimensional study","year":2025,"lang":"en","type":"article","venue":"Next research.","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Hydro-Québec","keywords":"Finite element method; Robustness (evolution); Artificial neural network; Nonlinear system; Residual; Bridging (networking); Convolution (computer science); Boundary (topology); Function (biology)","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":[0.001807956,0.0001199579,0.0001435765,0.00006389288,0.001127622,0.0002271944,0.0003349673,0.00002668456,0.0005935906],"category_scores_gemma":[0.00002126231,0.00008271137,0.00008804753,0.0005593447,0.00009235797,0.00008342038,0.0003267172,0.0007041212,0.00006389534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002944153,"about_ca_system_score_gemma":0.00009223774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002144937,"about_ca_topic_score_gemma":0.00002869396,"domain_scores_codex":[0.9974853,0.0008163436,0.0002457346,0.0003169123,0.0005316894,0.0006040357],"domain_scores_gemma":[0.9981574,0.001124808,0.00003681199,0.0004127003,0.0001692086,0.000099061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002964737,0.0007384425,0.008697075,0.00000669825,0.000350874,0.000004950245,0.0001908901,0.1178667,0.0002169566,0.1015438,0.1586003,0.6114868],"study_design_scores_gemma":[0.001870364,0.0004813147,0.007112826,0.00006373839,0.00005245162,6.785415e-7,0.002398113,0.5143385,0.000445475,0.0679127,0.4049553,0.0003685755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7184156,0.003131604,0.05308411,0.03815664,0.005749968,0.007878294,0.00002931516,0.0003357663,0.1732188],"genre_scores_gemma":[0.9852449,0.000012332,0.000589085,0.0001750461,0.0008558492,0.00016744,0.00000886394,0.00001241506,0.01293405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6111183,"threshold_uncertainty_score":0.8672868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1085745471777481,"score_gpt":0.4180582920148045,"score_spread":0.3094837448370563,"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."}}