{"id":"W4391547749","doi":"10.1109/lsp.2024.3362189","title":"Distributed Multi-Sensor Control for Multi-Target Tracking With a Sparsity-Promoting Objective Function","year":2024,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Guidance and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Aeronautical Science Foundation of China; China Scholarship Council","keywords":"Computer science; Function (biology); Tracking (education); Wireless sensor network; Control (management); Artificial intelligence; Computer network","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":[0.0002617266,0.0003093353,0.0003304727,0.0001229424,0.0002202418,0.0003503079,0.0001192193,0.00009602949,0.000003564003],"category_scores_gemma":[0.00001517793,0.0002714101,0.0001179696,0.0002727651,0.00004556366,0.0004681321,0.000004307704,0.0002915211,0.00001401838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001586604,"about_ca_system_score_gemma":0.00004077414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001556093,"about_ca_topic_score_gemma":0.00001337855,"domain_scores_codex":[0.9985276,0.00002864779,0.000312858,0.0004105115,0.0002089795,0.0005113363],"domain_scores_gemma":[0.9995413,0.00009519546,0.00006875781,0.0001054588,0.000107007,0.00008221943],"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":[0.0001927792,0.00004906219,0.0009959758,0.00149462,0.0004083155,0.00007475485,0.001496834,0.204497,0.7711306,0.00000339871,0.0004099285,0.01924672],"study_design_scores_gemma":[0.002034061,0.00008786212,0.0008019347,0.0007832741,0.000154216,0.00002393248,0.0002112694,0.9807124,0.01424982,0.000008702951,0.0005348742,0.000397638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1059276,0.001008027,0.8908713,0.0002004148,0.0004587371,0.0006075572,0.0000740066,0.000842838,0.000009549291],"genre_scores_gemma":[0.9954553,7.873807e-7,0.003408365,0.0002705503,0.0005297489,0.0001934822,0.00002614987,0.00009557665,0.00002009968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8895276,"threshold_uncertainty_score":0.9999738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966789064375946,"score_gpt":0.2299331753085077,"score_spread":0.2102652846647482,"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."}}