{"id":"W2166446045","doi":"10.1109/rtas.2010.40","title":"Using PCM in Next-generation Embedded Space Applications","year":2010,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Phase-change memory; Computer science; Dram; Embedded system; Memory controller; Dynamic random-access memory; Universal memory; Registered memory; CAS latency; Scalability; Interleaved memory; Interface (matter); Semiconductor memory; Computer memory; Computer hardware; Computer architecture; Operating system; 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":[0.0001804536,0.00006434903,0.00006437077,0.0001180065,0.00008444777,0.0001570955,0.0003557504,0.00005432872,0.00001395616],"category_scores_gemma":[0.00001609665,0.00006319319,0.00001837147,0.0003944353,0.00001488378,0.0003282776,0.00008705573,0.0001189909,0.0000152591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001466378,"about_ca_system_score_gemma":0.00004957683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004775732,"about_ca_topic_score_gemma":0.00006287322,"domain_scores_codex":[0.9994153,0.00002367627,0.0001360857,0.0002153867,0.00008841965,0.0001210715],"domain_scores_gemma":[0.9994741,0.00002046225,0.00004336107,0.0003703457,0.00005412196,0.00003762148],"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":[8.923762e-7,0.0001205219,0.0009555032,0.000005258971,0.0000035392,0.000001831402,0.0004341023,0.04179423,0.2679152,0.6625435,0.00145116,0.02477424],"study_design_scores_gemma":[0.00006251848,0.000004806472,0.000105096,0.0000016748,5.506408e-7,0.000004453999,0.00000411691,0.9785864,0.01773026,0.002222577,0.001191296,0.00008623784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01277534,0.00001006303,0.9801639,0.0003320645,0.00009468613,0.0001498834,1.180916e-7,0.0003529231,0.006121058],"genre_scores_gemma":[0.4285973,0.000002213407,0.5710875,0.0001076399,0.00005032875,0.00001247228,0.000001365016,0.000002735196,0.0001384967],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9367922,"threshold_uncertainty_score":0.2576943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07282726386613744,"score_gpt":0.3152569391735555,"score_spread":0.2424296753074181,"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."}}