{"id":"W4241574228","doi":"10.32920/ryerson.14657154","title":"Improving the Energy Efficiency by Cooperative Transmission in Multi-Hop Wireless Ad-Hoc Networks","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Wireless ad hoc network; Computer science; Computer network; Exploit; Quality of service; Mobile ad hoc network; Network packet; Physical layer; Distributed computing; Vehicular ad hoc network; Hop (telecommunications); Wireless; Telecommunications","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":[0.0009851017,0.0004566901,0.0004144905,0.0005196076,0.0003089357,0.0005892526,0.0006035304,0.0004887455,0.0004243402],"category_scores_gemma":[0.002935827,0.0002537961,0.0002763365,0.0008909374,0.0008791449,0.001239202,0.0006672009,0.0005233617,0.0001186826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005451784,"about_ca_system_score_gemma":0.0005049699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000936373,"about_ca_topic_score_gemma":0.001186746,"domain_scores_codex":[0.9994354,0.000277302,0.00001534998,0.00005399627,0.0001592099,0.00005878818],"domain_scores_gemma":[0.9987177,0.0009726578,0.00009948447,0.0000818148,0.0001040926,0.00002432519],"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":[0.00003475737,0.00005066928,0.0004703265,0.0001202254,0.00003767688,0.00008763044,0.0001430745,0.8719746,0.01015637,0.0794199,0.0007167992,0.03678793],"study_design_scores_gemma":[0.000006515389,0.00004649086,0.0001624931,0.000009202298,0.000008158968,0.00003144316,0.00002447208,0.9697841,0.002322386,0.02645071,0.001146909,0.000007242688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05875377,0.001073817,0.9348155,0.0002662802,0.00003286055,0.00003759867,0.00002400557,0.0001052322,0.004890948],"genre_scores_gemma":[0.9137693,0.001452571,0.08240935,0.00007204297,0.00005521456,0.00008109431,0.00003417157,0.00004090559,0.002085356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009851017,"threshold_uncertainty_score":0.005209744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02905886351235546,"score_gpt":0.2699700187757163,"score_spread":0.2409111552633608,"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."}}