{"id":"W1977258855","doi":"10.1109/trustcom.2013.236","title":"Mobile Parallel Computing Algorithms for Single-Buffered, Speed-Scalable Processors","year":2013,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scalability; Speedup; Parallel computing; Computation; Mobile device; Task (project management); Energy consumption; Distributed computing; Algorithm; Real-time computing; Computer hardware; Embedded system; Operating system","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":[0.0002800422,0.0002281288,0.0002627454,0.0001283049,0.0002607072,0.000505068,0.00102479,0.0001051757,0.00004306937],"category_scores_gemma":[0.00004697273,0.0001996732,0.0001002238,0.0004055518,0.00004406602,0.0005988181,0.0002948189,0.0001128284,0.0001135221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004740346,"about_ca_system_score_gemma":0.00004864598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005555612,"about_ca_topic_score_gemma":7.144563e-7,"domain_scores_codex":[0.9982429,0.00004026536,0.0003897749,0.0005642758,0.0002355561,0.0005272246],"domain_scores_gemma":[0.9987034,0.0001470472,0.0001522786,0.0004804295,0.0003722009,0.0001446294],"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":[0.00002368053,0.001475258,0.0009790304,0.0003321441,0.0001418843,0.00000955914,0.003522065,0.2611347,0.004753423,0.07311212,0.1700577,0.4844585],"study_design_scores_gemma":[0.000395923,0.0002833241,0.00003539681,0.00002532286,0.000003296789,0.0000147008,0.00003572529,0.9821919,0.006117968,0.00644686,0.004135589,0.0003140254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001715297,0.0001197523,0.9811182,0.000308345,0.0001838203,0.001024688,9.755835e-7,0.001721693,0.01380723],"genre_scores_gemma":[0.199018,0.000008552318,0.7972776,0.000456263,0.00009310088,0.00008675803,0.000006991768,0.00001969318,0.003033048],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7210572,"threshold_uncertainty_score":0.8142439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03030497818767171,"score_gpt":0.274289455638857,"score_spread":0.2439844774511853,"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."}}