{"id":"W4409445324","doi":"10.1007/s10915-025-02850-z","title":"Informed Normalized Gradient Flow Method for Parameterized Schrödinger Operators: A Case Study on Photonic Graphene","year":2025,"lang":"en","type":"article","venue":"Journal of Scientific Computing","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Carleton University","funders":"","keywords":"Parameterized complexity; Mathematics; Graphene; Flow (mathematics); Balanced flow; Schrödinger's cat; Mathematical analysis; Geometry; Quantum mechanics; Combinatorics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001578015,0.0001648361,0.0003650105,0.0004106946,0.0006103221,0.0004015288,0.000210064,0.00002608375,0.00004088342],"category_scores_gemma":[0.00004245754,0.0001284067,0.0003066964,0.0006546782,0.00004717844,0.0001645457,0.00007048246,0.0002610828,0.000001374202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004595635,"about_ca_system_score_gemma":0.0002039399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002276054,"about_ca_topic_score_gemma":0.000003739003,"domain_scores_codex":[0.9983866,0.0001216519,0.0007068063,0.0002537092,0.0002390008,0.0002922277],"domain_scores_gemma":[0.9985991,0.0003657874,0.0004001402,0.0002062937,0.0003116483,0.0001170776],"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":[0.001791442,0.004822255,0.01441422,0.0001969354,0.002016276,0.0004001565,0.01561181,0.2052066,0.02364072,0.004487185,0.01671056,0.7107019],"study_design_scores_gemma":[0.008357886,0.0007405069,0.0002658108,0.0004482766,0.0002593675,0.000278765,0.009342798,0.9638683,0.009899911,0.0008899687,0.005253766,0.0003946945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8388163,0.00002057437,0.157761,0.00006637585,0.002718237,0.0004341866,0.000003536677,0.00001144012,0.0001683934],"genre_scores_gemma":[0.9735371,5.041639e-7,0.02597363,0.0000564738,0.0002108532,0.000008738934,0.000002439706,0.000008672389,0.000201594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7586617,"threshold_uncertainty_score":0.5236275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03423342604364035,"score_gpt":0.3480933730604174,"score_spread":0.3138599470167771,"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."}}