{"id":"W1938489143","doi":"10.1109/aps.2015.7305067","title":"Monte Carlo based non-radiating objective function minimization for permittivity profile estimation","year":2015,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Monte Carlo method; Maxima and minima; Permittivity; Mathematical optimization; Function (biology); Statistical physics; Dynamic Monte Carlo method; Computer science; Physics; Mathematics; Mathematical analysis; Statistics; Dielectric","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00131498,0.0008583979,0.0008495686,0.0007892802,0.0004487832,0.0006686045,0.0008576976,0.001037224,0.001355835],"category_scores_gemma":[0.002989793,0.0005698501,0.0007228632,0.0005251407,0.0005644737,0.0007677858,0.0005815321,0.0009751563,0.0003777647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006485633,"about_ca_system_score_gemma":0.0008421105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002090377,"about_ca_topic_score_gemma":0.002796885,"domain_scores_codex":[0.999355,0.0002785001,0.00002511734,0.00006497173,0.0002368164,0.0000394981],"domain_scores_gemma":[0.9986455,0.0009397684,0.0001160344,0.00008813207,0.0001747845,0.00003574102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005681701,0.00004124999,0.0004641005,0.00006742555,0.00005160987,0.00005252069,0.00003098204,0.9455863,0.00768009,0.008378468,0.0003984559,0.03719201],"study_design_scores_gemma":[0.000002922367,0.000008719378,0.00006097899,0.000003537798,0.000003289754,0.00002052323,0.000001980405,0.9969004,0.001696031,0.00104368,0.0002523925,0.000005659346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002376829,0.00007027723,0.9970204,0.00002449411,0.000005869332,0.00001031288,0.000006295529,0.0001052236,0.0003803371],"genre_scores_gemma":[0.1582782,0.0002011749,0.8393757,0.00009484505,0.00002687481,0.0001461772,0.00009849757,0.0001713911,0.001607154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002090377,"threshold_uncertainty_score":0.006954372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01400345429775619,"score_gpt":0.2227065550833526,"score_spread":0.2087031007855964,"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."}}