{"id":"W2731280337","doi":"10.1145/3062341.3062371","title":"Low overhead dynamic binary translation on ARM","year":2017,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Royal Society of Canada","keywords":"Binary translation; Computer science; ARM architecture; Instruction set; Architecture; Overhead (engineering); Implementation; Compatibility (geochemistry); Parallel computing; Embedded system; Binary number; Computer architecture; Operating system; Programming language; Software; Arithmetic; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001302405,0.0000789444,0.00007461514,0.00006346848,0.0003256714,0.0002497276,0.0007621275,0.00004365608,0.00001413198],"category_scores_gemma":[0.00001523859,0.00006958631,0.00003916176,0.00004545977,0.00002463714,0.0003439131,0.00007177937,0.00006918712,0.00005735248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001834007,"about_ca_system_score_gemma":0.00001894509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001204896,"about_ca_topic_score_gemma":0.000004079047,"domain_scores_codex":[0.9993927,0.00002080793,0.0001031017,0.0002250226,0.0001329704,0.0001253911],"domain_scores_gemma":[0.9991095,0.00003028194,0.00007337316,0.0007217631,0.00002732568,0.00003775078],"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":[0.00002999862,0.0005722293,0.0004136823,0.00002875705,0.00002327582,0.000030272,0.0005675768,0.03644478,0.001541281,0.147133,0.008166604,0.8050486],"study_design_scores_gemma":[0.0001638876,0.0001243186,0.003303072,0.00002383444,8.597835e-7,0.000001979748,9.506355e-7,0.9894651,0.002625993,0.003486623,0.0006883515,0.0001150213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004312241,0.0000158054,0.9401698,0.001642466,0.0001707173,0.00007856794,3.900747e-7,0.0005558913,0.05305409],"genre_scores_gemma":[0.8380129,0.00002109999,0.1608636,0.0002517739,0.00001490743,0.000002972429,0.000001563875,0.000004277662,0.0008269145],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9530203,"threshold_uncertainty_score":0.2837647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02444214630360577,"score_gpt":0.2953209687064649,"score_spread":0.2708788224028592,"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."}}