{"id":"W2910103780","doi":"10.1109/access.2019.2892113","title":"A Novel Smeared Synthesized LFM TC-OLA Radar System: Design and Performance Evaluation","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Compute Canada; University of Victoria","funders":"","keywords":"Radar; Computer science; Continuous-wave radar; Pulse-Doppler radar; Pulse compression; Jamming; Waveform; Low probability of intercept radar; Electronic engineering; Radar imaging; Telecommunications; Engineering; 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":[0.0004334085,0.0004244677,0.000458385,0.0005026116,0.000253898,0.0005837198,0.0007814353,0.0005994667,0.002330026],"category_scores_gemma":[0.0005793119,0.0001518965,0.0002357559,0.0002963954,0.000176221,0.0007528551,0.0004015214,0.0003414744,0.0009135085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004011121,"about_ca_system_score_gemma":0.0004720883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006504256,"about_ca_topic_score_gemma":0.0005782907,"domain_scores_codex":[0.9994895,0.00008444217,0.00002990258,0.00009235077,0.0002666599,0.00003712369],"domain_scores_gemma":[0.9993446,0.00009046786,0.0001448775,0.00007751642,0.0002755352,0.00006696937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001168954,0.0003255966,0.004949437,0.0005811702,0.0001303125,0.0004517893,0.0003513254,0.02049905,0.6818067,0.004213976,0.002971978,0.2825498],"study_design_scores_gemma":[0.000314414,0.00635304,0.007331992,0.00006515011,0.0002109509,0.002426622,0.0001353565,0.5589015,0.3941395,0.0006180991,0.02938009,0.0001232036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2783015,0.001682132,0.7037137,0.0005383924,0.0002249286,0.0004791435,0.0001874028,0.003691958,0.01118095],"genre_scores_gemma":[0.7821733,0.0004592122,0.2106429,0.0002787256,0.0001194245,0.000184255,0.0002268914,0.00007986246,0.005835298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002330026,"threshold_uncertainty_score":0.007794738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03581020001087488,"score_gpt":0.2545555797442845,"score_spread":0.2187453797334096,"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."}}