{"id":"W2063358347","doi":"10.1145/2818950.2818970","title":"Architecture Exploration for Data Intensive Applications","year":2015,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Computer science; Compass; Flexibility (engineering); Architecture; Computer architecture; Software; Software architecture; Embedded system; Computer architecture simulator; Distributed computing; Operating 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002426515,0.0005678064,0.0002807447,0.0003544419,0.0004890952,0.000552584,0.0008497661,0.0004557655,0.004560636],"category_scores_gemma":[0.0008749762,0.0003223544,0.0005412622,0.0003332066,0.0003357377,0.0008036967,0.0007809377,0.0006812873,0.0005816167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005061414,"about_ca_system_score_gemma":0.0008182022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002314921,"about_ca_topic_score_gemma":0.003289666,"domain_scores_codex":[0.9998585,0.00004243302,0.000005581332,0.00001791728,0.00005724808,0.00001827082],"domain_scores_gemma":[0.9997206,0.0001361613,0.00002091006,0.0000426831,0.00005669576,0.00002289106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001893865,0.00009922266,0.003400318,0.0003217394,0.00005467438,0.0002381379,0.0002306246,0.8748132,0.01733887,0.0463221,0.004636899,0.05235485],"study_design_scores_gemma":[0.00002587678,0.00007388269,0.000398389,0.00002757658,0.00001726802,0.00009173836,0.00006046005,0.9517029,0.007676849,0.01827008,0.0216403,0.00001476839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2888237,0.002703932,0.6546509,0.001238386,0.0001523923,0.0002505532,0.0009416139,0.003484795,0.04775367],"genre_scores_gemma":[0.6993248,0.001668523,0.286235,0.0002478993,0.00003299245,0.0002714101,0.001044472,0.0005760904,0.01059872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004560636,"threshold_uncertainty_score":0.01525688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1482648559649719,"score_gpt":0.3432189633478697,"score_spread":0.1949541073828978,"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."}}