{"id":"W2729263255","doi":"10.1007/978-3-319-61566-0_19","title":"Single Hop Selection Based Forwarding in WDFAD-DBR for Under Water Wireless Sensor Networks","year":2017,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer network; Packet forwarding; Computer science; Network packet; Hop (telecommunications); Routing protocol; Forwarder; Virtual routing and forwarding; Energy consumption; Wireless sensor network; Distributed computing; Dynamic Source Routing","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004447406,0.0003844766,0.0006711442,0.000213354,0.0001891207,0.000240814,0.000248018,0.0003176235,0.000004442337],"category_scores_gemma":[0.000002402647,0.0003528165,0.0001155301,0.00002720397,0.0000409985,0.0001688058,0.0000842115,0.0003768368,0.00000318154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00026445,"about_ca_system_score_gemma":0.00001259143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006326638,"about_ca_topic_score_gemma":0.0002800799,"domain_scores_codex":[0.9981552,0.00004368948,0.0008199097,0.0004032184,0.0001510658,0.0004269606],"domain_scores_gemma":[0.9990752,0.000199113,0.0002060142,0.0003640861,0.0000972015,0.00005837963],"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":[0.00001547133,0.00001732998,0.0003231101,0.0009331729,0.00006209902,0.000005541311,0.0002895834,0.9445992,0.0005010125,0.002518601,0.00001132814,0.05072359],"study_design_scores_gemma":[0.0003469667,0.00004302764,0.000005667526,0.003592483,0.00001893814,0.00002210168,0.0003226627,0.8834081,0.001567865,0.0005344703,0.1095953,0.0005425155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003472843,0.01896463,0.9604136,0.00002509064,0.001192497,0.0009532251,0.00000686527,0.0001631827,0.01480806],"genre_scores_gemma":[0.9932624,0.001375208,0.000809625,0.00001985285,0.0003852005,0.00004677474,0.00004996057,0.0001089614,0.003942091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9897895,"threshold_uncertainty_score":0.9998924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02681629601191052,"score_gpt":0.2523820287673867,"score_spread":0.2255657327554762,"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."}}