{"id":"W2048124977","doi":"10.1155/2015/532676","title":"Delay-Sensitive Routing Schemes for Underwater Acoustic Sensor Networks","year":2015,"lang":"en","type":"article","venue":"International Journal of Distributed Sensor Networks","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Dalhousie University","funders":"King Saud University","keywords":"Computer science; End-to-end delay; Routing (electronic design automation); Propagation delay; Transmission delay; Network delay; Computer network; Transmission (telecommunications); Static routing; Underwater; Routing protocol; Throughput; Underwater acoustics; Real-time computing; Telecommunications; Network packet","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":[],"consensus_categories":[],"category_scores_codex":[0.0004952722,0.0002424158,0.0003578453,0.000116512,0.00007253011,0.0002073059,0.000494799,0.0001853794,0.000007847959],"category_scores_gemma":[0.00004244186,0.0002185592,0.0002233636,0.0001405643,0.0000495363,0.0002389123,0.00007617618,0.0004362386,0.000008546057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003385374,"about_ca_system_score_gemma":0.00004159251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006552778,"about_ca_topic_score_gemma":0.00000670282,"domain_scores_codex":[0.9981213,0.00009108752,0.0008461867,0.000147973,0.0004247177,0.0003686954],"domain_scores_gemma":[0.997479,0.0002770685,0.0003399735,0.0001961552,0.001477683,0.0002300715],"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":[0.0001592107,0.00003799764,0.0005027674,0.000006316751,0.0006063222,0.00006072113,0.0001340978,0.9934282,0.0008694514,0.00008468289,0.00229652,0.001813688],"study_design_scores_gemma":[0.001650305,0.0000850727,0.0001673823,0.0001687478,0.00008514793,0.0005813061,0.0007954284,0.9649503,0.001272985,0.0001096892,0.02984044,0.0002931931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05437636,0.0004143194,0.9431009,0.0003458425,0.001303142,0.0001612997,0.00006783671,0.0001303946,0.00009992773],"genre_scores_gemma":[0.9925159,0.0001158115,0.005349965,0.0001320098,0.001628948,0.000006796861,0.0001366392,0.00006561651,0.00004830414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9381396,"threshold_uncertainty_score":0.8912586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02589885231781799,"score_gpt":0.2560660297998505,"score_spread":0.2301671774820325,"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."}}