{"id":"W4386914957","doi":"10.36227/techrxiv.24162906.v1","title":"Radar Near-Field Sensing Using Metasurface for Biomedical Applications","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Radar; Field (mathematics); Computer science; Remote sensing; Electronic engineering; Systems engineering; Engineering; Telecommunications; Geology","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":[0.0003109939,0.0004465737,0.0004041514,0.0002690381,0.0001213841,0.0007261428,0.0003411361,0.0009574001,0.001535033],"category_scores_gemma":[0.0006035978,0.0002361146,0.0003421986,0.0003102326,0.0004509361,0.0009603703,0.0006657572,0.0006453902,0.0007587853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003316414,"about_ca_system_score_gemma":0.0001706922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007277205,"about_ca_topic_score_gemma":0.0001225997,"domain_scores_codex":[0.999719,0.00005198154,0.00001158659,0.00004630915,0.0001524222,0.00001873982],"domain_scores_gemma":[0.9997221,0.000103802,0.00003897674,0.00006856352,0.00005292184,0.00001372558],"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":[0.00005823857,0.00001891657,0.0001948846,0.0001433562,0.00002224139,0.0000875855,0.00004817982,0.009701218,0.9445791,0.02058236,0.0005333226,0.02403053],"study_design_scores_gemma":[0.00003114,0.0002422347,0.000690001,0.00005254257,0.00003330858,0.0008097328,0.00007895189,0.308596,0.6338497,0.0325776,0.022994,0.00004486829],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1282508,0.005704856,0.8424882,0.00151282,0.0004012231,0.0000450445,0.0001271029,0.0009282429,0.0205416],"genre_scores_gemma":[0.7141864,0.00259679,0.2749073,0.0003467726,0.0001595269,0.00004187068,0.0001072524,0.0001871431,0.007466962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001535033,"threshold_uncertainty_score":0.005135179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05374559892260259,"score_gpt":0.2910342441379709,"score_spread":0.2372886452153683,"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."}}