{"id":"W4402811802","doi":"10.1109/iccc62479.2024.10681893","title":"Signal Enhancing: Bi-Static ISAC with IRS-Mounted Target","year":2024,"lang":"en","type":"article","venue":"","topic":"Infrared Target Detection Methodologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Computer science; SIGNAL (programming language)","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":[0.0002702227,0.0007179234,0.0003942521,0.0002739086,0.0002636279,0.0005104588,0.0007453326,0.0005038201,0.0006552553],"category_scores_gemma":[0.0005172024,0.0001676919,0.0002718292,0.000517543,0.0006608561,0.0007866679,0.0007642378,0.0004136212,0.00026937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003256624,"about_ca_system_score_gemma":0.0004481605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008881992,"about_ca_topic_score_gemma":0.001524188,"domain_scores_codex":[0.9996605,0.00007064263,0.000009064947,0.0000793159,0.0001273272,0.00005326673],"domain_scores_gemma":[0.9997182,0.00007532239,0.00008104539,0.00004249097,0.00005800742,0.00002479715],"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":[0.0003732485,0.0001591798,0.002128004,0.0002150092,0.00006916866,0.0004740833,0.0003067277,0.435737,0.3768529,0.0193996,0.001766905,0.1625181],"study_design_scores_gemma":[0.0000102094,0.0002620576,0.0004089456,0.000006404545,0.00002107728,0.0001918825,0.0000512248,0.9572876,0.03883861,0.001543239,0.001360301,0.00001843043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1729446,0.0004413482,0.8126324,0.0002473337,0.00006544347,0.00004324303,0.00002660706,0.0004633386,0.01313567],"genre_scores_gemma":[0.9080735,0.0001802373,0.08891884,0.0001105021,0.00002575351,0.00003146345,0.00002707863,0.00001927654,0.002613327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008881992,"threshold_uncertainty_score":0.002362847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01806037024539809,"score_gpt":0.2609740627729227,"score_spread":0.2429136925275246,"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."}}