{"id":"W4402968328","doi":"10.1109/ap-s/inc-usnc-ursi52054.2024.10685997","title":"Near-Field Scanning System for Enhanced Bio-Sensing at Low Frequencies","year":2024,"lang":"en","type":"article","venue":"","topic":"Microwave and Dielectric Measurement Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Materials science; Acoustics; Physics","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":[0.0002809833,0.0003077384,0.0003414941,0.0002805869,0.0002556411,0.0003036394,0.000605432,0.0006698642,0.003372473],"category_scores_gemma":[0.0005077771,0.0002078783,0.0001642887,0.0001745681,0.0002639302,0.0006081788,0.0005296039,0.0004179544,0.001286414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002084527,"about_ca_system_score_gemma":0.0002851254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001992889,"about_ca_topic_score_gemma":0.0003147823,"domain_scores_codex":[0.9997187,0.00005120087,0.00001506031,0.00006482341,0.0001338359,0.00001634215],"domain_scores_gemma":[0.9997428,0.00008451287,0.00004541769,0.00003606443,0.00007119231,0.00002011128],"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":[0.0001155716,0.00003368101,0.0003649064,0.0001596155,0.000008342679,0.0001261962,0.0001095717,0.0007675661,0.9511904,0.002450366,0.001241667,0.04343205],"study_design_scores_gemma":[0.00006214999,0.001180565,0.002973045,0.00006586678,0.00005270674,0.002774887,0.00009910403,0.04437636,0.8879954,0.001406662,0.05892158,0.00009171824],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2241492,0.002653462,0.7554247,0.0009163353,0.0005353282,0.0003397404,0.0002600178,0.002934077,0.0127871],"genre_scores_gemma":[0.6387975,0.001052625,0.346623,0.0007113341,0.0001615889,0.0003107109,0.0002070254,0.00009368345,0.01204255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003372473,"threshold_uncertainty_score":0.01128203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581850550879092,"score_gpt":0.2257090651056038,"score_spread":0.2098905595968129,"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."}}