{"id":"W2609732805","doi":"10.2528/pier16122204","title":"ANTENNA CALIBRATION METHOD FOR DIELECTRIC PROPERTY ESTIMATION OF BIOLOGICAL TISSUES AT MICROWAVE FREQUENCIES","year":2017,"lang":"en","type":"article","venue":"Electromagnetic waves","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Alberta Innovates - Technology Futures","keywords":"Microwave; Calibration; Antenna (radio); Property (philosophy); Dielectric; Acoustics; Estimation; Materials science; Remote sensing; Electronic engineering; Computer science; Physics; Telecommunications; Mathematics; Optoelectronics; Engineering; Geology; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002098295,0.0001701958,0.000287677,0.00008230221,0.0002290372,0.0000850217,0.0002274384,0.00008037662,0.00003043889],"category_scores_gemma":[0.0001794338,0.0001223739,0.0001039789,0.00007817693,0.0000878667,0.0001090911,0.00002988772,0.00007852862,0.000004965741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005279792,"about_ca_system_score_gemma":0.00001394513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009198236,"about_ca_topic_score_gemma":0.00002704533,"domain_scores_codex":[0.9990842,0.00004162055,0.0002677657,0.0002212324,0.00008951704,0.0002956761],"domain_scores_gemma":[0.9993716,0.00007919398,0.0001030263,0.0003557292,0.00004762769,0.00004281556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000125457,0.00001263533,0.000147388,0.00007213764,0.000047841,0.000001130966,0.0001330786,0.0004069951,0.9783528,0.00005296711,0.0006713218,0.0200892],"study_design_scores_gemma":[0.0001489163,0.0002278995,0.001567534,0.00002050226,0.00004437074,0.0000152146,0.000005719861,0.4876539,0.5090343,0.0009487877,0.0001857748,0.0001470893],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6761586,0.002260804,0.3189746,0.0005553762,0.0001181004,0.0003621584,0.00002013093,0.0002280513,0.001322145],"genre_scores_gemma":[0.9217743,0.0001768578,0.07672209,0.00001563128,0.00005258349,0.00003095547,0.00003553264,0.00002304121,0.001168976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4872469,"threshold_uncertainty_score":0.4990263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01998398155212004,"score_gpt":0.2613132107672145,"score_spread":0.2413292292150944,"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."}}