{"id":"W4254060415","doi":"10.4108/icst.wicon2008.4793","title":"Multi-Objective Scheduling for MUD based Ad-Hoc Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Quality of service; Wireless ad hoc network; Computer network; Scheduling (production processes); Throughput; Mobile ad hoc network; Ad hoc wireless distribution service; Adaptive quality of service multi-hop routing; Distributed computing; Vehicular ad hoc network; Optimized Link State Routing Protocol; Wireless; Network packet; Telecommunications; 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":[0.001234221,0.0007146339,0.0008162592,0.0005132437,0.0005399933,0.0006937099,0.0008372682,0.0004180555,0.001711144],"category_scores_gemma":[0.002118069,0.0003773435,0.0002337655,0.0007626539,0.0004455659,0.000637105,0.0006034255,0.0005426203,0.0002408648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008894357,"about_ca_system_score_gemma":0.0009310348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002388204,"about_ca_topic_score_gemma":0.002889753,"domain_scores_codex":[0.9994925,0.0002385503,0.00002173162,0.00005328907,0.0001208431,0.0000730867],"domain_scores_gemma":[0.9991196,0.0005401237,0.0001189679,0.00003317653,0.0001093774,0.00007883766],"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":[0.00007724977,0.00004156501,0.0002323884,0.0000769878,0.00004642717,0.0000570475,0.00003030162,0.9618825,0.001031722,0.00894478,0.001005021,0.02657403],"study_design_scores_gemma":[0.00001389724,0.00002829079,0.00005639343,0.000004180663,0.000005502258,0.000008042585,0.000007141308,0.9951429,0.0001866464,0.004021665,0.0005217721,0.000003483138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03810541,0.001465301,0.9546444,0.0002937557,0.0001925185,0.000109617,0.00009886274,0.0002384514,0.004851704],"genre_scores_gemma":[0.8597518,0.0008677678,0.1342109,0.0001139255,0.000154554,0.0002389007,0.0001474348,0.00006974456,0.004445058],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002388204,"threshold_uncertainty_score":0.006527245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04112892908099854,"score_gpt":0.278174013002121,"score_spread":0.2370450839211224,"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."}}