{"id":"W2071761886","doi":"10.1145/2465351.2465366","title":"Whose cache line is it anyway?","year":2013,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Cache; Cache coloring; Cache pollution; Parallel computing; Cache algorithms; Operating system; CPU cache; Page cache; Smart Cache; Parallelism (grammar); Central processing unit; Software; Embedded 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001170004,0.0000836626,0.00008478222,0.00006036461,0.00007087007,0.0001874179,0.0005986828,0.00004587407,0.0004208316],"category_scores_gemma":[0.0000187587,0.00006761088,0.00003537734,0.0002257492,0.00001589106,0.0003407002,0.0002038515,0.00007073036,0.0007824396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001156272,"about_ca_system_score_gemma":0.00002229586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001222145,"about_ca_topic_score_gemma":0.000001496913,"domain_scores_codex":[0.9993066,0.00002534875,0.0001454979,0.0002252926,0.000126769,0.0001704675],"domain_scores_gemma":[0.9993225,0.00003287267,0.00003831182,0.0004243967,0.0001096532,0.00007223894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[4.89622e-7,0.00006856214,0.0002729558,0.000005274902,0.000009817955,0.000002299291,0.0007847679,0.001012575,0.0002667495,0.02059068,0.9287169,0.04826896],"study_design_scores_gemma":[0.0001116555,0.00005498743,0.0003393026,0.000008495228,0.000001132403,0.000005657825,0.00001200944,0.9593852,0.01007425,0.004653783,0.02517687,0.0001766562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009617885,0.00003805031,0.9447442,0.01042622,0.00007222022,0.00009820701,1.875459e-7,0.0006728952,0.04298617],"genre_scores_gemma":[0.3026694,0.00002678287,0.668562,0.008766589,0.00005212447,0.00001455121,0.000001091485,0.00000603322,0.01990147],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9583727,"threshold_uncertainty_score":0.9999956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02853846785902747,"score_gpt":0.2761337980008055,"score_spread":0.247595330141778,"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."}}