{"id":"W4405662613","doi":"10.1007/s10586-024-04831-7","title":"Time delay-based routing protocol using genetic algorithm in vehicular Ad Hoc networks","year":2024,"lang":"en","type":"article","venue":"Cluster Computing","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Computer network; Routing protocol; Node (physics); Scalability; Distributed computing; Wireless ad hoc network; Routing (electronic design automation)","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":[0.0006261945,0.0004385307,0.0004077766,0.0002553684,0.0001294898,0.0002901789,0.0003045084,0.0002612418,0.00003119142],"category_scores_gemma":[0.0000142831,0.0004782657,0.0001689971,0.0007907015,0.00005111417,0.0001460412,0.0001869669,0.0008100318,0.0000838835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004297254,"about_ca_system_score_gemma":0.00007621344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005751572,"about_ca_topic_score_gemma":0.000004945752,"domain_scores_codex":[0.9973071,0.000147866,0.0006942695,0.0005640711,0.0002894783,0.0009972582],"domain_scores_gemma":[0.9991722,0.0001868534,0.00005946297,0.0003885593,0.00004226296,0.0001506901],"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":[0.000004765799,0.00001326418,0.00007112446,0.0001804344,0.00004123817,0.0003857618,0.0001589294,0.8978658,0.0001102431,0.000001202613,0.0001700782,0.1009971],"study_design_scores_gemma":[0.0007057493,0.0000311695,0.000151436,0.001357999,0.00003233081,0.0001250234,0.00001402713,0.9940717,0.00005611518,0.00001350834,0.002925384,0.0005155821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09197352,0.00202249,0.8888642,0.00002583389,0.0006106987,0.01514744,0.000002388689,0.00119862,0.0001548115],"genre_scores_gemma":[0.7612411,0.000006885061,0.2323966,0.0003394607,0.001937867,0.003456218,0.00004372811,0.0005250067,0.00005320461],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6692675,"threshold_uncertainty_score":0.9997669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008539897106455684,"score_gpt":0.2361596937848201,"score_spread":0.2276197966783644,"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."}}