{"id":"W4256473940","doi":"10.1145/2872887.2750398","title":"SLIP","year":2015,"lang":"en","type":"article","venue":"ACM SIGARCH Computer Architecture News","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Security Agency","keywords":"Cache; Computer science; Dram; Parallel computing; CPU cache; Energy consumption; Slip (aerodynamics); Cache algorithms; Memory hierarchy; Efficient energy use; Embedded system; Operating system; Computer hardware; Engineering; Electrical 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004819788,0.0002964095,0.0002988715,0.0003036779,0.0001398958,0.0003133265,0.003552644,0.000106741,0.000005693086],"category_scores_gemma":[0.0001966281,0.0002571197,0.0001238897,0.000651803,0.00007191866,0.000254686,0.002101901,0.0004174654,0.0001111137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006046952,"about_ca_system_score_gemma":0.0001886782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005244131,"about_ca_topic_score_gemma":0.00001008537,"domain_scores_codex":[0.997573,0.0002626221,0.0003500357,0.0006998727,0.0005703559,0.0005441476],"domain_scores_gemma":[0.9970964,0.0002801529,0.0001124021,0.00188612,0.000201652,0.0004233044],"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":[0.00001879198,0.0001298734,0.0009469491,0.00001665829,0.00004508148,0.00007358683,0.003989128,0.07537054,0.00009030598,0.01221528,0.1241274,0.7829764],"study_design_scores_gemma":[0.001735989,0.0009685522,0.001217832,0.00007897624,0.00001181174,0.0003874469,0.00001551276,0.5243706,0.001915429,0.1741727,0.2940014,0.001123742],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002065884,0.0001275207,0.9852242,0.00560074,0.0006855085,0.000248193,0.00000103216,0.001716076,0.004330866],"genre_scores_gemma":[0.07850557,0.000008126471,0.917362,0.003255662,0.0005999215,0.00001829663,0.000007407224,0.00002352832,0.0002194911],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7818527,"threshold_uncertainty_score":0.9999881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03076761984409592,"score_gpt":0.2738943726696939,"score_spread":0.243126752825598,"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."}}