{"id":"W2639531913","doi":"10.1109/ccece.2017.7946662","title":"A framework for extending resources of embedded systems using the Cloud","year":2017,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Cloud computing; Scalability; Distributed computing; Scheduling (production processes); Computation; Computer data storage; Database; Operating system; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009592604,0.00009790109,0.0001634286,0.00004441095,0.0009235224,0.0005778437,0.002022784,0.00004585859,0.000001386162],"category_scores_gemma":[0.0002017691,0.00005943834,0.0001000682,0.0000743756,0.00008173004,0.0000250987,0.0007665526,0.00008382274,0.000001654195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001700818,"about_ca_system_score_gemma":0.00001142897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001659785,"about_ca_topic_score_gemma":0.000001716195,"domain_scores_codex":[0.9990163,0.00006115737,0.0002190813,0.0002500273,0.0002199284,0.0002334515],"domain_scores_gemma":[0.9978256,0.0003634929,0.0003218846,0.001397909,0.00005485782,0.00003627986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009817704,0.0000433737,0.0004729309,0.0001229801,0.00008435625,0.000003896334,0.003427837,0.0302841,0.000205568,0.9418092,0.0006075064,0.02292837],"study_design_scores_gemma":[0.0001423629,0.00003411041,0.0003305226,0.0001870512,0.00001359336,0.000005854725,0.0006369993,0.9835956,0.0002206865,0.00778284,0.00693931,0.0001110589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1648788,0.0002093007,0.8308752,0.0005463762,0.00101996,0.0002521795,4.686758e-7,0.00007125733,0.002146452],"genre_scores_gemma":[0.9214941,0.000001041342,0.07729703,0.000060698,0.0003809221,0.000007564573,4.657765e-8,0.000007415835,0.0007511458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9533115,"threshold_uncertainty_score":0.7103081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05844054904494322,"score_gpt":0.3252209869967215,"score_spread":0.2667804379517783,"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."}}