{"id":"W2560324125","doi":"10.1109/mascots.2016.49","title":"Experimental Calibration and Validation of a Speed Scaling Simulator","year":2016,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Speedup; Scaling; Context (archaeology); Energy consumption; Simulation; Real-time computing; Parallel computing","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":[0.00009183693,0.00004015612,0.00005405157,0.00004483909,0.00002720408,0.00002872691,0.0001002032,0.00002101135,0.000009517516],"category_scores_gemma":[0.00001615943,0.00002689024,0.00001221822,0.00007057695,0.00001730351,0.0003039182,0.0000667971,0.000009072395,9.30945e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008149234,"about_ca_system_score_gemma":0.000009326482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005158145,"about_ca_topic_score_gemma":3.714642e-8,"domain_scores_codex":[0.9996098,0.00002339698,0.0001153944,0.0001185231,0.00007949727,0.00005333798],"domain_scores_gemma":[0.9997423,0.00004233205,0.0000468437,0.000115824,0.00002855815,0.0000241466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001990467,0.000164668,0.004563692,0.00001738879,0.00001930314,0.000001428698,0.001452122,0.01301001,0.7852193,0.1633035,0.0008345636,0.03139407],"study_design_scores_gemma":[0.0001123534,0.00002169969,0.00006281796,0.000008929059,3.733915e-7,7.836544e-7,0.000003651968,0.363896,0.6353768,0.000469157,0.00001372028,0.00003368316],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.18694,0.00001713047,0.8123882,0.000138752,0.00002380462,0.00004181766,1.761065e-7,0.000140369,0.0003097041],"genre_scores_gemma":[0.8973735,0.000002057807,0.1024935,0.00003395658,0.000009481981,5.909545e-7,3.078892e-7,0.000001939794,0.00008467934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7104335,"threshold_uncertainty_score":0.1096552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01952134201757961,"score_gpt":0.2739885478817611,"score_spread":0.2544672058641815,"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."}}