{"id":"W4391694250","doi":"10.1002/9781119825883.ch6","title":"Frequency‐domain Characterization of Signals and Systems","year":2024,"lang":"en","type":"other","venue":"","topic":"Advanced Electrical Measurement Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Calgary","funders":"","keywords":"Characterization (materials science); Frequency domain; Domain (mathematical analysis); Computer science; Mathematics; Materials science; Nanotechnology; Computer vision","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":[0.00004828296,0.0001304111,0.0002040266,0.0001722727,0.000002148569,0.00001097995,0.00004681063,0.0001482054,0.0001410325],"category_scores_gemma":[0.000004205394,0.0001161507,0.00001692783,0.0001100547,0.00001142978,0.00002168903,0.000007167854,0.0000832707,0.00002440161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002802923,"about_ca_system_score_gemma":0.000003223368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001290195,"about_ca_topic_score_gemma":0.000002092849,"domain_scores_codex":[0.9995344,0.000008788779,0.0001496865,0.0001114944,0.0001050449,0.00009055633],"domain_scores_gemma":[0.9998257,0.000004110866,0.00003162876,0.0001054199,0.00001004475,0.00002313957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[3.07073e-7,0.000004160719,0.000006296496,0.001617259,0.00007451117,0.000002645692,0.00001158148,0.000002805243,0.9174016,0.006273158,0.0736852,0.0009204561],"study_design_scores_gemma":[0.0003253745,0.0002031253,0.00006187714,0.007566287,0.0002002837,0.00002155378,0.00002283754,0.003031989,0.1516239,0.02598434,0.8089888,0.00196959],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00007624134,0.00696447,0.1899139,0.000008817876,0.000244698,0.000448967,0.00004126307,0.002541719,0.7997599],"genre_scores_gemma":[0.05816649,0.003913576,0.02046394,0.00003290025,0.0006569592,0.0002857149,0.0001089453,0.002784805,0.9135867],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7657777,"threshold_uncertainty_score":0.4736488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113335476871641,"score_gpt":0.2215849914616627,"score_spread":0.2102514437744986,"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."}}