{"id":"W7131677892","doi":"10.23919/piers-fall62445.2025.11394361","title":"A Statistically-Bounded Machine Learning Framework for Robust Full-Wave Electromagnetic Inversion","year":2025,"lang":"","type":"article","venue":"","topic":"Wireless Signal Modulation Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Interpretability; Bounded function; Inversion (geology); Inverse problem; Stability (learning theory); Heuristic; Statistical learning theory; Probably approximately correct learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007137149,0.0004784423,0.0005079657,0.0005016119,0.0009394303,0.0009111517,0.0008158384,0.0004395878,0.0006194054],"category_scores_gemma":[0.001804678,0.0005142374,0.0001982361,0.001726979,0.0002098908,0.0004802223,0.0003808344,0.0008596095,0.0001081269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004693176,"about_ca_system_score_gemma":0.0006553553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006496584,"about_ca_topic_score_gemma":0.00005047626,"domain_scores_codex":[0.995749,0.000420179,0.0009725856,0.001359575,0.0006264104,0.0008722756],"domain_scores_gemma":[0.995354,0.002460059,0.0004002318,0.000857257,0.0006782042,0.0002502237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002029038,0.0002049813,0.0001761947,0.0002116026,0.00007770304,0.00000449239,0.0002733778,0.00559636,0.006943835,0.8941296,0.0008935671,0.09128541],"study_design_scores_gemma":[0.0008437458,0.0008925188,0.001438613,0.0002265835,0.0000848746,0.000004488954,0.0000440261,0.8414146,0.001161207,0.1518646,0.001611662,0.0004130527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003047369,0.0003716592,0.9825718,0.009674232,0.0009490393,0.001271938,0.00001508258,0.0003124736,0.001786381],"genre_scores_gemma":[0.4629528,0.00005462886,0.5314577,0.0006325109,0.00008540171,0.00007765817,0.00004380183,0.00002429129,0.004671259],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8358183,"threshold_uncertainty_score":0.9997309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03737623260682944,"score_gpt":0.2727330318152745,"score_spread":0.2353567992084451,"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."}}