{"id":"W3126051646","doi":"10.1049/sil2.12011","title":"Robust Wiener filter‐based time gating method for detection of shallowly buried objects","year":2021,"lang":"en","type":"article","venue":"IET Signal Processing","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Constant false alarm rate; Clutter; Wiener filter; Computer science; Gating; Filter (signal processing); Detector; Artificial intelligence; Object detection; Pattern recognition (psychology); Computer vision; Matched filter; Algorithm; Radar; Telecommunications","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":[0.0004720114,0.0006682943,0.0006912997,0.0006717655,0.0001774153,0.000517886,0.0005621242,0.0005468198,0.001203138],"category_scores_gemma":[0.0008745123,0.000279105,0.0005267416,0.0003820944,0.0003170022,0.0006113144,0.0005554071,0.0005030041,0.0006462008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002634937,"about_ca_system_score_gemma":0.0006021684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006295759,"about_ca_topic_score_gemma":0.0006815984,"domain_scores_codex":[0.9996425,0.00005593006,0.00002322021,0.00007844254,0.0001646689,0.00003518202],"domain_scores_gemma":[0.999666,0.00009377763,0.00006465978,0.00004124195,0.0001081092,0.00002616054],"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":[0.0003181564,0.00008851495,0.0008170972,0.0001231216,0.00006599065,0.0001447042,0.0001122373,0.04156248,0.471953,0.008729073,0.0008243246,0.4752613],"study_design_scores_gemma":[0.00002177543,0.000232734,0.001600563,0.00001816056,0.00004871512,0.0003267936,0.00001831651,0.8625963,0.1294025,0.002418317,0.003267863,0.00004793512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01053866,0.0001266231,0.9887043,0.00001876196,0.00002131398,0.00001434703,0.00001314547,0.0002753781,0.0002874236],"genre_scores_gemma":[0.246715,0.0003893082,0.7494062,0.00007032904,0.00004736109,0.0000721028,0.0001384204,0.0000792078,0.003082152],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001203138,"threshold_uncertainty_score":0.004024923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02873601252571304,"score_gpt":0.2744822630936334,"score_spread":0.2457462505679204,"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."}}