{"id":"W2724658019","doi":"10.1049/el.2017.1784","title":"Methodology to determine window length for unknown target detection in electronic warfare system","year":2017,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Window (computing); Detector; SIGNAL (programming language); Detection theory; Computer science; Signal processing; Algorithm; Telecommunications; Computer hardware; Digital signal processing","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008242688,0.0002452227,0.0003890602,0.0001867234,0.0002880935,0.000123757,0.0003887859,0.0001310766,0.000002412351],"category_scores_gemma":[0.00009457675,0.0002571548,0.00009378302,0.0001048256,0.00001935047,0.0002198206,0.00002695176,0.0003599212,0.000009654655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008315242,"about_ca_system_score_gemma":0.00005389583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004889212,"about_ca_topic_score_gemma":0.0007495136,"domain_scores_codex":[0.9981536,0.0000815064,0.0003384151,0.0003337205,0.0001312513,0.0009614556],"domain_scores_gemma":[0.9992754,0.0001024638,0.00009645671,0.000414216,0.0000329621,0.00007850012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001148132,0.00001307891,0.0002256604,0.0005786256,0.0001167079,0.0000200151,0.000423013,0.03796355,0.9140811,0.001412745,0.0004121441,0.04463854],"study_design_scores_gemma":[0.002835971,0.0007203168,0.001211794,0.0003534951,0.00008070912,0.0001807692,0.0001567114,0.2644613,0.6436708,0.0007186962,0.084095,0.001514394],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6194146,0.001246976,0.377262,0.0004902621,0.000576849,0.0005783157,0.000003827822,0.0002242898,0.000202902],"genre_scores_gemma":[0.9963033,0.0000155806,0.002937725,0.0001633896,0.0003000904,0.0001592023,0.000004677797,0.00007678905,0.00003925747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3768887,"threshold_uncertainty_score":0.9999881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02381708789186452,"score_gpt":0.2557208429289407,"score_spread":0.2319037550370762,"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."}}