{"id":"W1965380876","doi":"10.1109/joe.2013.2239812","title":"Robust Spatial Reuse Scheduling in Underwater Acoustic Communication Networks","year":2013,"lang":"en","type":"article","venue":"IEEE Journal of Oceanic Engineering","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Network topology; Computer science; Reuse; Robustness (evolution); Distributed computing; Computer network; Scheduling (production processes); Underwater acoustic communication; Underwater; Propagation delay; Network packet; Topology (electrical circuits); Engineering","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":[0.001510421,0.0003797337,0.0005547694,0.0006572859,0.0006033349,0.000713405,0.0009800447,0.0004271983,0.0004766689],"category_scores_gemma":[0.003836296,0.0002665849,0.0002442892,0.0009607921,0.0007728607,0.0008424015,0.000832516,0.0004367603,0.0001502103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456967,"about_ca_system_score_gemma":0.001468536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003543044,"about_ca_topic_score_gemma":0.003151628,"domain_scores_codex":[0.9991271,0.0003148323,0.00004293173,0.0001027519,0.0003022234,0.0001103105],"domain_scores_gemma":[0.9983341,0.0009751802,0.0002606567,0.0001719426,0.0002040766,0.00005407093],"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":[0.00006788456,0.00002329588,0.0003211783,0.00004925302,0.00001974657,0.00009167664,0.00006486696,0.9221558,0.005491004,0.04221129,0.0006067005,0.0288973],"study_design_scores_gemma":[0.000004554153,0.00001835399,0.00005674753,0.000002881221,0.000004357606,0.00001604556,0.00001175305,0.9908441,0.0009744283,0.007683999,0.0003787259,0.000004097755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04209164,0.0006676844,0.9545172,0.0001528246,0.0000486533,0.00003678559,0.0000345628,0.0002072169,0.002243492],"genre_scores_gemma":[0.9263514,0.0005318869,0.07158598,0.00005765927,0.00006610327,0.00006490019,0.00004366394,0.00003901682,0.001259339],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003543044,"threshold_uncertainty_score":0.01057106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169616463061673,"score_gpt":0.1946157447285335,"score_spread":0.1776540984223662,"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."}}