{"id":"W4399621218","doi":"10.1109/radarconf2458775.2024.10548987","title":"Multi-Sub-Chirp Signal Synthesis for Millimeter-Wave Radar Based on Dechirp Processing","year":2024,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Chirp; Extremely high frequency; Computer science; SIGNAL (programming language); Radar; Signal processing; Millimeter; Electronic engineering; Telecommunications; Physics; Engineering; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003051431,0.0002955332,0.0002887121,0.0002185176,0.0001641641,0.0003449854,0.0001228915,0.0001291116,0.00006120408],"category_scores_gemma":[0.00003951933,0.0002420417,0.0001723832,0.0002262727,0.00002398015,0.0002126293,0.000009673686,0.000172265,0.0000396678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009452352,"about_ca_system_score_gemma":0.0000730976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007489436,"about_ca_topic_score_gemma":0.000007773554,"domain_scores_codex":[0.9986452,0.00002174373,0.0003433523,0.0003643467,0.0002390506,0.0003862394],"domain_scores_gemma":[0.9993057,0.0003481575,0.00002559157,0.0001683153,0.00004158932,0.0001105916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006836978,0.0001030904,0.00001844346,0.005795198,0.0001675842,0.0001019174,0.0003882699,0.0368393,0.2098036,0.0001100781,0.005067247,0.741537],"study_design_scores_gemma":[0.0001940622,0.00004437997,0.00001302233,0.0008443829,0.00003984013,0.000009292033,0.00004846726,0.8654808,0.1292147,0.00004844658,0.003753794,0.0003088489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009168131,0.002204684,0.9830941,0.00008839395,0.0004164801,0.0003897568,0.00003299765,0.001109115,0.003496341],"genre_scores_gemma":[0.9455091,0.000005807905,0.05368233,0.00008119296,0.0002451359,0.000102618,0.0000065279,0.0001179896,0.0002492565],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.936341,"threshold_uncertainty_score":0.9870173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02818842846741368,"score_gpt":0.2346304526544749,"score_spread":0.2064420241870612,"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."}}