{"id":"W1964718088","doi":"10.1109/tmc.2012.100","title":"Underwater Localization with Time-Synchronization and Propagation Speed Uncertainties","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":141,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Underwater; Benchmark (surveying); Synchronization (alternating current); Node (physics); Underwater acoustic communication; Global Positioning System; Radio propagation; Real-time computing; Propagation delay; Underwater acoustics; Network packet; Algorithm; Channel (broadcasting); Telecommunications; Computer network; Acoustics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007492154,0.000665808,0.0007174309,0.000565127,0.0004110366,0.0006697359,0.0009858186,0.0008276413,0.000622004],"category_scores_gemma":[0.003280703,0.0003597893,0.0003621688,0.0009578094,0.0005525522,0.001295595,0.001240525,0.0005703864,0.0002201605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006104291,"about_ca_system_score_gemma":0.001039007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005559357,"about_ca_topic_score_gemma":0.003215989,"domain_scores_codex":[0.9993746,0.0001504356,0.00003448598,0.0001208655,0.0002690576,0.00005071393],"domain_scores_gemma":[0.9988897,0.0005362861,0.0002019705,0.0001471365,0.0001978562,0.00002703908],"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":[0.00007814129,0.00001532281,0.0006289734,0.00005110857,0.00002401866,0.0000706663,0.00006434216,0.9261615,0.005009678,0.008121194,0.00042257,0.05935241],"study_design_scores_gemma":[0.00001157742,0.00002657834,0.0001422273,0.000002732701,0.000006230769,0.00003883861,0.000008536789,0.9948633,0.002299107,0.001973324,0.0006218654,0.000005646812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0130051,0.00009208472,0.9858536,0.00004229945,0.00001718851,0.00001173801,0.00001453729,0.0002627393,0.0007007384],"genre_scores_gemma":[0.6449612,0.000324167,0.35146,0.00004126271,0.0000575892,0.00008558219,0.0001229942,0.00007266016,0.002874509],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005559357,"threshold_uncertainty_score":0.01105398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097947883319094,"score_gpt":0.2077546191934288,"score_spread":0.1967751403602379,"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."}}