{"id":"W2567191584","doi":"10.1109/cisis.2016.110","title":"A Reliable and Interference-Aware Routing Protocol for Underwater Wireless Sensor Networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Dalhousie University","funders":"","keywords":"Computer network; Computer science; Routing protocol; Geographic routing; Forwarder; Dynamic Source Routing; Network packet; Wireless Routing Protocol; Zone Routing Protocol; Source routing; Wireless sensor network; Equal-cost multi-path routing; Path vector protocol","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":[0.0001108001,0.0001154558,0.0001303745,0.00002572475,0.00006559549,0.00006910998,0.0001244961,0.00006943109,0.00003932512],"category_scores_gemma":[5.917072e-7,0.00006871635,0.00002840837,0.00003808039,0.00002037544,0.0001102793,0.00005860877,0.00005016277,0.00001122726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003293157,"about_ca_system_score_gemma":0.000004904247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001250752,"about_ca_topic_score_gemma":0.00001863063,"domain_scores_codex":[0.9993694,0.00001264471,0.0002193979,0.0001321792,0.00004503344,0.000221331],"domain_scores_gemma":[0.9996026,0.0000531082,0.00002496877,0.0002236439,0.00004279406,0.00005289555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008923444,0.0003723627,0.07217719,0.0041703,0.001090484,0.00001141489,0.004602057,0.0137334,0.3080871,0.01882644,0.02188539,0.5541515],"study_design_scores_gemma":[0.004428231,0.0002076667,0.0003528964,0.001247501,0.00001679809,0.0000294889,0.0005942973,0.7185911,0.07488287,0.0009655149,0.1978161,0.0008675832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005675705,0.000003839615,0.9649338,0.0002075191,0.00002656794,0.02765981,0.000002203923,0.0003373341,0.001153254],"genre_scores_gemma":[0.9293402,0.000003664483,0.001812651,0.00003515162,0.00005619139,0.06703985,0.000001082807,0.00002951753,0.001681733],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9631211,"threshold_uncertainty_score":0.2802171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03167003712409956,"score_gpt":0.257402239521773,"score_spread":0.2257322023976735,"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."}}