{"id":"W3211419629","doi":"10.1002/wcm.656","title":"Placement of multiple mobile data collectors in underwater acoustic sensor networks","year":2008,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Underwater; Routing (electronic design automation); Computer network; Real-time computing; Propagation delay; Relay; Solver; Wireless sensor network; Distributed computing","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":[],"consensus_categories":[],"category_scores_codex":[0.0002805253,0.0001547023,0.0002905836,0.0001122967,0.0002578317,0.00002662933,0.0009976667,0.00007669602,0.000004739738],"category_scores_gemma":[0.000002431232,0.0001575094,0.00002847464,0.0002888812,0.0001521957,0.00009685296,0.0009891182,0.0002366211,0.000002722219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005700405,"about_ca_system_score_gemma":0.00002236375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002061993,"about_ca_topic_score_gemma":0.0002507282,"domain_scores_codex":[0.9987949,0.0001320974,0.0005459951,0.0001930598,0.0001042365,0.0002297351],"domain_scores_gemma":[0.9974298,0.0003874134,0.00009151994,0.001978226,0.00005537398,0.00005759541],"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":[0.000009894068,0.0002349975,0.02535137,0.0001257317,0.00007924978,0.000002215056,0.004116232,0.9440601,0.01047598,0.00001660845,0.0001477332,0.01537983],"study_design_scores_gemma":[0.000495226,0.00003399956,0.001113168,0.0001124987,0.000008983717,0.00001763908,0.001491909,0.9909173,0.0004716257,0.000001914032,0.005164434,0.0001713296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.930927,0.003737822,0.06428602,0.00001466992,0.00004500256,0.0005588322,0.00001741457,0.0001816667,0.0002315398],"genre_scores_gemma":[0.9912859,0.003674456,0.004773634,0.00001192561,0.00001905389,0.00008388858,0.00008254575,0.0000386555,0.0000299013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06035891,"threshold_uncertainty_score":0.6423048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04147099955713176,"score_gpt":0.2571595667270497,"score_spread":0.2156885671699179,"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."}}