{"meta":{"query_hash":"68e86217d3fa","filters":{"venue":"2022 Photonics & Electromagnetics Research Symposium (PIERS)"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/68e86217d3fa","api":"https://metacan.xera.ac/api/v1/cohort?venue=2022+Photonics+%26amp%3B+Electromagnetics+Research+Symposium+%28PIERS%29"},"results":[{"id":"W4282975696","doi":"10.1109/piers55526.2022.9792648","title":"Recent Advances in Novel Training Approaches for Microwave Parametric Modeling Using Padé via Lanczos and EM Sensitivities","year":2022,"lang":"en","type":"article","venue":"2022 Photonics & Electromagnetics Research Symposium (PIERS)","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Parametric statistics; Robustness (evolution); Pole–zero plot; Artificial neural network; Algorithm; Transfer function; Sensitivity (control systems); Mathematics; Parametric model; Parametric equation; Control theory (sociology); Computer science; Geometry; Artificial intelligence; Engineering; Electronic engineering","score_opus":0.1550788121043189,"score_gpt":0.3543148983490759,"score_spread":0.19923608624475703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282975696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8220929,0.03307679,0.14137354,0.00026153278,0.0002573306,0.0016275392,0.00007093214,0.00018522848,0.0010541921],"genre_scores_gemma":[0.83278483,0.011536483,0.15429637,0.00010052167,0.00008399403,0.000643797,0.00011627464,0.00020430861,0.0002334459],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9956114,0.0005289407,0.0006195504,0.00074057153,0.0009257636,0.0015737468],"domain_scores_gemma":[0.9977738,0.0012882939,0.000077290795,0.0004349907,0.0001780062,0.00024760794],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002605884,0.0003970752,0.000581231,0.0010985616,0.00057237875,0.00015684287,0.00034390565,0.00015999484,0.000072923634],"category_scores_gemma":[0.00033751904,0.00047816668,0.000115420255,0.0024698586,0.00012916989,0.00017412644,0.00023188032,0.0015330516,0.0000015087289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017356788,0.00012886361,0.000018219269,0.0001380099,0.000045991586,0.0000062713216,0.0031512876,0.46149737,0.49269077,0.00035592596,0.00003161327,0.041762125],"study_design_scores_gemma":[0.0010863479,0.00073952967,0.00000806306,0.000018020923,0.00003074957,0.000089126625,0.0014890488,0.97169006,0.004354977,0.0023901688,0.017591028,0.0005128749],"about_ca_topic_score_codex":0.00002737047,"about_ca_topic_score_gemma":0.0001289302,"teacher_disagreement_score":0.5101927,"about_ca_system_score_codex":0.0009238405,"about_ca_system_score_gemma":0.00027325994,"threshold_uncertainty_score":0.999767},"labels":[],"label_agreement":null}]}