{"id":"W3208714418","doi":"10.1109/ds-rt52167.2021.9576145","title":"An algorithm for threading assignment in large-scale wireless network mobile simulations","year":2021,"lang":"en","type":"article","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Compute Canada","keywords":"Synchronizing; Computer science; Thread (computing); Synchronization (alternating current); Multithreading; Parallel computing; Threading (protein sequence); Wireless; Wireless network; Distributed computing; Algorithm; Real-time computing; Computer network; Transmission (telecommunications)","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003038746,0.0001216751,0.0001972994,0.0000346824,0.0001789483,0.0001602466,0.0003018626,0.00008291154,0.00008475985],"category_scores_gemma":[0.000001082063,0.0001183661,0.00005614268,0.0003689047,0.00001449704,0.0003235063,0.0001172563,0.00009945817,0.000006092846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004443569,"about_ca_system_score_gemma":0.0001143852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008642577,"about_ca_topic_score_gemma":0.0001343565,"domain_scores_codex":[0.9986258,0.00005517692,0.0002736136,0.0004226175,0.0001733922,0.0004494701],"domain_scores_gemma":[0.9990625,0.000207497,0.00005009575,0.0004569521,0.00008346028,0.0001395034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005156836,0.0004913531,0.002713295,0.000008148547,0.00001974516,0.00006590126,0.0006615405,0.1404067,0.00004617426,0.02530173,0.002029929,0.8282503],"study_design_scores_gemma":[0.0004255589,0.0000740535,0.0001112732,0.00001896057,0.000004999437,0.000005251123,0.0001383926,0.9918507,0.0000711218,0.004488262,0.002645086,0.0001663277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002626517,0.00009464988,0.9949378,0.00009858415,0.0004298514,0.0002715139,0.00001469165,0.0001031718,0.00142318],"genre_scores_gemma":[0.7223437,0.00001068838,0.2762795,0.0004270253,0.0002195572,0.00005645734,0.0000531137,0.000009878534,0.0006000747],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.851444,"threshold_uncertainty_score":0.4826831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01802541997935773,"score_gpt":0.2802570105182854,"score_spread":0.2622315905389277,"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."}}