{"id":"W2132082977","doi":"10.1109/radar.2008.4720784","title":"Impact of measurement model mismatch on nonlinear Track-Before-Detect performance","year":2008,"lang":"en","type":"article","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Clutter; Computer science; Constant false alarm rate; Radar; Rayleigh distribution; Stationary target indication; Moving target indication; Sensitivity (control systems); Rayleigh scattering; Artificial intelligence; Radar tracker; Radar horizon; Algorithm; Radar imaging; Electronic engineering; Pulse-Doppler radar; Engineering; Telecommunications; Optics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003171227,0.0001878318,0.0002271104,0.00009947619,0.0001518665,0.00002582823,0.0007459461,0.00007788851,0.00003076917],"category_scores_gemma":[0.00002378672,0.0001332619,0.0001657165,0.0002789688,0.00005271257,0.0002880764,0.00009629322,0.0001884084,0.00006087646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007109222,"about_ca_system_score_gemma":0.0001307061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003919261,"about_ca_topic_score_gemma":0.000004395869,"domain_scores_codex":[0.9982143,0.00003048059,0.0003310912,0.0003540169,0.0007405021,0.0003296145],"domain_scores_gemma":[0.9987113,0.00003003982,0.0001019719,0.0008354586,0.0001993761,0.0001217802],"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":[0.0002276724,0.001107747,0.01169242,0.00007317343,0.0001493898,0.00004195615,0.002511509,0.74997,0.004609648,0.001777266,0.02901778,0.1988215],"study_design_scores_gemma":[0.0003542137,0.0005259567,0.01223402,0.0000357497,0.000003212057,0.00003307015,0.000002137926,0.9810873,0.005261296,0.0001277513,0.0001695575,0.0001656809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7859924,0.00003822378,0.2084945,0.0000616593,0.0001679429,0.0001229669,0.000009003108,0.0002225699,0.004890696],"genre_scores_gemma":[0.9279162,0.00004999936,0.07170862,0.00008138438,0.00007464128,0.000003819392,0.000002979225,0.00001190777,0.0001504644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2311174,"threshold_uncertainty_score":0.5434262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04638847759983412,"score_gpt":0.2586574277249303,"score_spread":0.2122689501250962,"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."}}