{"id":"W4390832969","doi":"10.1109/tits.2024.3351442","title":"Current Effect-Eliminated Optimal Target Assignment and Motion Planning for a Multi-UUV System","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Component (thermodynamics); Motion planning; Key (lock); Underwater; Computer science; Path (computing); Unmanned underwater vehicle; Motion (physics); Distributed computing; Real-time computing; Artificial intelligence; Robot; Computer network; Computer security","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000345975,0.0003280906,0.000342406,0.0003132528,0.0001864789,0.0002181607,0.0001351742,0.0001458459,0.00000938972],"category_scores_gemma":[3.600751e-7,0.0003063093,0.0001705168,0.0002357405,0.0000274941,0.0002147843,3.165753e-7,0.0002718274,0.00003752851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002641985,"about_ca_system_score_gemma":0.00001469549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003841482,"about_ca_topic_score_gemma":0.000008232657,"domain_scores_codex":[0.9982408,0.00009076343,0.0007463321,0.0003694168,0.0002693368,0.0002833441],"domain_scores_gemma":[0.9993424,0.0001549755,0.00005566044,0.0002341077,0.00007967757,0.0001331218],"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":[0.00007459926,0.00008480836,0.00007389181,0.005075774,0.0003212947,0.000007604242,0.005067572,0.9559597,0.005566304,0.0002459954,0.00005429679,0.02746813],"study_design_scores_gemma":[0.0005171617,0.0001678736,0.00009216323,0.00178714,0.0001505677,0.00001689501,0.001639912,0.9184548,0.06496716,0.000002012727,0.01184558,0.0003587923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04289652,0.003919378,0.9482408,0.00001219883,0.002153544,0.001444657,0.0002660056,0.001046938,0.00001995794],"genre_scores_gemma":[0.9971326,0.0001756897,0.0009684787,0.000002706534,0.00007097637,0.001367786,0.0001044872,0.00008391315,0.00009337643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9542361,"threshold_uncertainty_score":0.9999389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04018799223746691,"score_gpt":0.2857341648584694,"score_spread":0.2455461726210025,"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."}}