{"id":"W2091907331","doi":"10.1145/2818950.2818974","title":"HpMC","year":2015,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"European Commission; Lawrence Livermore National Laboratory; U.S. Department of Energy; Advanced Micro Devices; National Science Foundation","keywords":"Computer science; Dram; Embedded system; Memory controller; Energy consumption; Efficient energy use; Memory management; Distributed computing; Computer architecture; Semiconductor memory; Computer hardware; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001298989,0.00002861558,0.00003163754,0.00002875788,0.00001725113,0.00005233075,0.00033316,0.0000135631,0.000004087321],"category_scores_gemma":[0.00001962371,0.00002343542,0.00001019605,0.0001260886,0.000005621114,0.0001322035,0.0001035493,0.00002131826,0.0001012248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000836187,"about_ca_system_score_gemma":0.00002726958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007640821,"about_ca_topic_score_gemma":3.150492e-7,"domain_scores_codex":[0.9996996,0.00001367086,0.00004977634,0.00008891285,0.00008067843,0.00006738572],"domain_scores_gemma":[0.9996794,0.000008225658,0.00001207496,0.0001915012,0.000049904,0.00005885895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[8.658228e-7,0.00003019807,0.0004587755,9.354589e-7,0.000002867267,0.00000461209,0.0003603931,0.003864187,0.00001578659,0.7020036,0.2612327,0.03202511],"study_design_scores_gemma":[0.0001687678,0.00005554371,0.0001355951,0.000002393379,4.460827e-7,0.00001234414,0.000008294714,0.8909536,0.002718566,0.03514138,0.07067346,0.0001296278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001276036,0.00001826712,0.8456141,0.0005665956,0.00007276332,0.00001608339,1.582597e-8,0.0007699365,0.1528146],"genre_scores_gemma":[0.2182566,0.000001247111,0.7786739,0.000545727,0.00001791092,0.000001283351,2.045942e-7,0.000001424767,0.002501607],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8870894,"threshold_uncertainty_score":0.1301074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04137170615660445,"score_gpt":0.2765564288034216,"score_spread":0.2351847226468172,"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."}}