{"id":"W3105987688","doi":"10.1109/tbcas.2020.3038589","title":"Non-Invasive Real-Time Monitoring of Glucose Level Using Novel Microwave Biosensor Based on Triple-Pole CSRR","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Circuits and Systems","topic":"Microwave and Dielectric Measurement Techniques","field":"Engineering","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; C-COM Satellite Systems","keywords":"Materials science; Microwave; Microstrip; Split-ring resonator; Biosensor; Dielectric; Optoelectronics; Network analyzer (electrical); Substrate (aquarium); Resonator; Coplanar waveguide; Planar; Waveguide; Electronic engineering; Computer science; Telecommunications; Nanotechnology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002282265,0.0002699447,0.0004550587,0.0002755008,0.000102384,0.0000392607,0.0001317389,0.0002261531,0.00001716178],"category_scores_gemma":[0.00001436137,0.0002507415,0.0001226743,0.0004597634,0.00007334987,0.00006019235,0.000001024302,0.0002462399,0.00001126807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001007161,"about_ca_system_score_gemma":0.00007641913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001007322,"about_ca_topic_score_gemma":0.000001278893,"domain_scores_codex":[0.9983721,0.00003694154,0.0005225913,0.000319431,0.0004285497,0.0003203689],"domain_scores_gemma":[0.9992179,0.0001215424,0.00008092768,0.0002069372,0.00007711822,0.0002956093],"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":[0.0000235933,0.0001242148,0.00001436145,0.0004013222,0.00007243032,0.000007190986,0.0001731222,0.0015687,0.9941559,0.000005323313,0.0001657476,0.003288034],"study_design_scores_gemma":[0.001018859,0.0003731152,0.00004462824,0.0004790145,0.00006231606,0.00001077604,0.00008431228,0.09824798,0.8991963,0.000001492734,0.0002099768,0.0002712983],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1925016,0.0001683306,0.8048444,0.00004962911,0.0006561899,0.0005773085,0.0002157608,0.0002849852,0.0007018316],"genre_scores_gemma":[0.998915,0.0001389561,0.0006240649,0.00004280001,0.0001750288,0.00002274295,0.000005985863,0.0000457329,0.00002973132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8064134,"threshold_uncertainty_score":0.9999945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06529552085602149,"score_gpt":0.2481059106878206,"score_spread":0.1828103898317991,"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."}}