{"id":"W3215833533","doi":"10.1145/3479239.3485694","title":"A Novel Harvesting-Aware RL-based Opportunistic Routing Protocol for Underwater Sensor Networks","year":2021,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Routing protocol; Computer network; Forwarder; Network packet; Underwater; Wireless sensor network; Underwater acoustic communication; Wireless Routing Protocol; Dynamic Source Routing; Efficient energy use; Link-state routing protocol; Energy harvesting; Energy (signal processing); Engineering; Electrical 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":[0.0005926038,0.0005400651,0.0005979639,0.0004537913,0.0005553595,0.0004910046,0.00151445,0.0004557466,0.0005784056],"category_scores_gemma":[0.001308781,0.0002419934,0.0004308792,0.0004738015,0.0003751266,0.0009334913,0.001246215,0.0006188965,0.0001798379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003893902,"about_ca_system_score_gemma":0.0009531616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001479124,"about_ca_topic_score_gemma":0.003228921,"domain_scores_codex":[0.9995885,0.000110772,0.00003899161,0.00007342594,0.0001314662,0.00005684396],"domain_scores_gemma":[0.9994612,0.0002375721,0.00008903831,0.00006706137,0.0001122286,0.0000328862],"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":[0.0003575496,0.0002263144,0.001566028,0.0004869429,0.0002287818,0.0008257919,0.0003892394,0.5603555,0.07156182,0.03373669,0.008935554,0.3213297],"study_design_scores_gemma":[0.00002220575,0.0001411833,0.0001951083,0.00001441167,0.00003627281,0.0002540793,0.00004599682,0.9855132,0.004561227,0.003986248,0.005199309,0.00003077596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02232199,0.0009901315,0.9712772,0.000324573,0.0001881044,0.0001435298,0.00009652914,0.0006340611,0.004023795],"genre_scores_gemma":[0.7842928,0.001213901,0.2081407,0.0003638411,0.0001137789,0.0004011905,0.0002905085,0.0001007474,0.005082372],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00151445,"threshold_uncertainty_score":0.003134012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07986701636017103,"score_gpt":0.2877626675892781,"score_spread":0.2078956512291071,"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."}}