{"id":"W2766748441","doi":"10.1145/3149412.3149415","title":"Execution Phase Prediction Based on Phase Precursors and Locality","year":2017,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Locality; Computer science; Workload; Phase (matter); Overhead (engineering); Power (physics); Locality of reference; Real-time computing; Parallel computing; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003332573,0.00009334568,0.00008906078,0.00006687336,0.0004438469,0.000318774,0.0003905941,0.00005351778,0.000009365336],"category_scores_gemma":[0.00008079666,0.00008231414,0.00002627065,0.00004940161,0.00006344829,0.0004027002,0.00008751768,0.0000739862,0.000006053209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002231541,"about_ca_system_score_gemma":0.00002716477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000263296,"about_ca_topic_score_gemma":0.000001130345,"domain_scores_codex":[0.9992239,0.00005172021,0.0001358546,0.0003050944,0.0001568803,0.000126474],"domain_scores_gemma":[0.9990509,0.0000319576,0.0001047251,0.0006769203,0.00005636182,0.00007911171],"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":[0.0003542811,0.003731552,0.002476522,0.00006696248,0.00003352381,0.00002544569,0.0005287249,0.02104222,0.001020543,0.08196662,0.03614844,0.8526052],"study_design_scores_gemma":[0.001573251,0.0004248713,0.0005217703,0.00002084539,0.000002883343,0.000001757849,0.000001496213,0.9891111,0.005884899,0.0009899861,0.001377248,0.00008987972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009928915,0.000007726547,0.9779475,0.0007953332,0.0001396486,0.0001472823,0.000004092834,0.0005788883,0.01045062],"genre_scores_gemma":[0.9291893,0.000008344842,0.07031428,0.0002550199,0.00003318252,0.000009130682,0.000005600102,0.000003616453,0.0001815795],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9680689,"threshold_uncertainty_score":0.3413757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02796785373942695,"score_gpt":0.3297933651926018,"score_spread":0.3018255114531748,"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."}}