{"id":"W2388380161","doi":"","title":"Analysis of Preemptive Scheduling Policy in Embedded μC/OS- II","year":2005,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Preemption; Scheduling (production processes); Parallel computing; Operating system; Embedded system; Computer security; Distributed computing; Mathematical optimization","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000266264,0.000172228,0.0003759521,0.0008693733,0.0001401438,0.00008073982,0.001240997,0.00008038804,0.000006262428],"category_scores_gemma":[0.000001720747,0.0001818774,0.0001810877,0.004018395,0.00004161575,0.0002104253,0.0004526232,0.0001393904,0.00003921777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001035192,"about_ca_system_score_gemma":0.0001102884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001209594,"about_ca_topic_score_gemma":0.00005316215,"domain_scores_codex":[0.9983593,0.00006346494,0.000562873,0.0005161709,0.0001783263,0.0003198652],"domain_scores_gemma":[0.9987965,0.00008974991,0.0002213494,0.0006884641,0.0001177419,0.00008614946],"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":[0.000006487086,0.0009967188,0.006397772,0.00005311273,0.0007556623,0.000002085927,0.009547329,0.5862538,0.005149725,0.1260461,0.0007910391,0.2640002],"study_design_scores_gemma":[0.0005761053,0.00004161703,0.01813802,0.00004309109,0.00008714115,0.000008351759,0.00003789681,0.8762254,0.001437398,0.0008363873,0.1021757,0.0003929943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04231349,0.0001513375,0.9548255,0.0007071121,0.00001220075,0.0003996825,0.00002201153,0.0001362658,0.001432396],"genre_scores_gemma":[0.7239162,0.000004194401,0.2755478,0.0001648238,0.0001468654,0.0000846477,0.00003652526,0.000006342335,0.00009265658],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6816027,"threshold_uncertainty_score":0.7416745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000879553326459,"score_gpt":0.2739798205193554,"score_spread":0.2639710249860908,"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."}}