{"id":"W2358092795","doi":"","title":"Small Target Detection in Sea Clutter Background Based on Doppler Spectrum Characteristics","year":2008,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clutter; Doppler effect; Constant false alarm rate; Rayleigh distribution; Stationary target indication; Moving target indication; Radar; Waveform; Remote sensing; Detector; Doppler radar; Computer science; Geology; Continuous-wave radar; Rayleigh scattering; Physics; Artificial intelligence; Radar imaging; Optics; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009740551,0.0001332256,0.0001537085,0.0001127918,0.00005531265,0.00003094663,0.0000585396,0.0000771941,0.000178036],"category_scores_gemma":[0.000004379773,0.0001215613,0.00003442354,0.0001348585,0.00001169173,0.00007941313,0.00000520721,0.000169925,0.0000929829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009705428,"about_ca_system_score_gemma":0.00001283664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000799937,"about_ca_topic_score_gemma":0.0001152062,"domain_scores_codex":[0.9992977,0.00001766944,0.0002133252,0.0001399923,0.0001120732,0.0002192132],"domain_scores_gemma":[0.9997718,0.00002531798,0.00002047418,0.0001230731,0.00001061472,0.00004866644],"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":[0.0006990871,0.001024216,0.2544325,0.00311361,0.0002512104,0.002340243,0.003329296,0.5037299,0.1733117,0.0005399412,0.01692662,0.04030172],"study_design_scores_gemma":[0.000506483,0.00006258777,0.0578475,0.00005984572,0.000003038895,0.00004312704,0.00002806169,0.9149301,0.02219333,0.00003831384,0.003963184,0.0003244424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8687438,0.00002374136,0.1193383,0.00006202084,0.0003969126,0.0001070442,0.000003922527,0.0002009262,0.01112325],"genre_scores_gemma":[0.998446,0.000003796873,0.0008598932,0.0001610692,0.0002025378,0.000007226762,0.00000682861,0.0000315864,0.0002810445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4112002,"threshold_uncertainty_score":0.4957124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02349483932196243,"score_gpt":0.193989342000991,"score_spread":0.1704945026790286,"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."}}