{"id":"W2148177244","doi":"10.1007/978-3-319-07425-2_18","title":"Energy Efficient Stable Routing Using Adjustable Transmission Ranges in Mobile Ad Hoc Networks","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Computer network; Mobile ad hoc network; Optimized Link State Routing Protocol; Wireless Routing Protocol; Routing protocol; Wireless ad hoc network; Destination-Sequenced Distance Vector routing; Ad hoc wireless distribution service; Distributed computing; Dynamic Source Routing; Routing (electronic design automation); Wireless; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002078702,0.0008927231,0.00106189,0.0009868529,0.0004098661,0.0006897688,0.003799341,0.0006936408,0.00003693147],"category_scores_gemma":[0.00002682314,0.0008483032,0.0002031665,0.001490332,0.0004765773,0.000449192,0.001508884,0.001337768,0.000007351685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008086819,"about_ca_system_score_gemma":0.0005965624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000644359,"about_ca_topic_score_gemma":0.0001642977,"domain_scores_codex":[0.9933019,0.0001544478,0.001015635,0.002533816,0.001284053,0.001710129],"domain_scores_gemma":[0.9962956,0.0007826688,0.0004941746,0.001866463,0.0002241336,0.0003369625],"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":[0.000006997795,0.00002030875,0.000007498011,0.00001853913,0.000003542613,0.00004061223,0.0002500469,0.5389779,0.00006569386,0.001442904,0.000006432424,0.4591595],"study_design_scores_gemma":[0.0005035981,0.0001743291,0.00001017344,0.001258701,0.00001070664,0.00004982463,4.996887e-7,0.9826888,0.0004943398,0.004234756,0.00966772,0.0009064903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002468187,0.01753553,0.9788189,0.00007720613,0.001785029,0.0006100656,0.000001778941,0.0002088084,0.0007158641],"genre_scores_gemma":[0.5069246,0.002004166,0.4873629,0.001585061,0.001227575,0.00008212109,0.00001573477,0.0001984659,0.0005994397],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5066777,"threshold_uncertainty_score":0.9993968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01203748230677721,"score_gpt":0.2256551037008887,"score_spread":0.2136176213941115,"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."}}