{"id":"W2016713259","doi":"10.4018/jssci.2010040105","title":"A Least-Laxity-First Scheduling Algorithm of Variable Time Slice for Periodic Tasks","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University","funders":"","keywords":"Computer science; Scheduling (production processes); Algorithm; Task (project management); Dynamic priority scheduling; Earliest deadline first scheduling; Rate-monotonic scheduling; Mathematical optimization; Mathematics; Computer network; Quality of service","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":[],"consensus_categories":[],"category_scores_codex":[0.001861152,0.0001458963,0.0002206958,0.0004372547,0.000299721,0.0003474154,0.001822696,0.00005815924,0.00002340407],"category_scores_gemma":[0.001351009,0.0001352977,0.00009539791,0.0006454034,0.0005760776,0.0009430351,0.0003467213,0.0003201941,0.000007300591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005303833,"about_ca_system_score_gemma":0.0008630709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001471023,"about_ca_topic_score_gemma":0.000001982449,"domain_scores_codex":[0.9976298,0.00002322384,0.0005930876,0.0003366702,0.001172498,0.0002447424],"domain_scores_gemma":[0.9918509,0.001021262,0.0005236044,0.0001403275,0.006300563,0.0001633517],"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":[0.0000605545,0.0002462584,0.0008702782,0.0000236503,0.00009901963,0.00001862908,0.001076403,0.07725459,0.001843252,0.04698429,0.0001613371,0.8713617],"study_design_scores_gemma":[0.0002779874,0.0002432909,0.00151824,0.0001928009,0.00001216742,0.0005337764,0.00006210071,0.9398139,0.001883824,0.05410378,0.001157391,0.0002008165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02331069,0.0001241259,0.9743231,0.0005720509,0.001448632,0.00009888199,0.00001393937,0.00002727304,0.00008133205],"genre_scores_gemma":[0.4530807,0.00001406374,0.5464234,0.0002194959,0.0002334798,0.000002557967,0.00000197187,0.00000496218,0.00001938916],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8711609,"threshold_uncertainty_score":0.5517281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336327353218105,"score_gpt":0.2805500619703307,"score_spread":0.2671867884381496,"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."}}