{"id":"W1987780915","doi":"10.1145/1347375.1347379","title":"Compile-time and instruction-set methods for improving floating- to fixed-point conversion accuracy","year":2008,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Algorithm; Scaling; Compile time; Floating point; Adder; Fixed point; Parallel computing; Subtraction; Parameterized complexity; Instruction set; Context (archaeology); Compiler; Arithmetic; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001148498,0.0003133604,0.0005226178,0.0002636178,0.001075084,0.0002206963,0.0008390039,0.0001240502,0.00000576736],"category_scores_gemma":[0.0003738595,0.0002982899,0.0001560242,0.0006560962,0.00007120455,0.0003841941,0.00008085505,0.0002980109,0.00002656654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001101582,"about_ca_system_score_gemma":0.00006785993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001598405,"about_ca_topic_score_gemma":4.10255e-7,"domain_scores_codex":[0.997318,0.0004825713,0.0006229885,0.0008205681,0.0002658801,0.0004900506],"domain_scores_gemma":[0.9958168,0.00253526,0.00025497,0.0008960686,0.0002087541,0.0002881029],"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":[0.00004761846,0.0001074042,0.00001686555,0.0001647623,0.00007717605,0.000006951474,0.003567094,0.01860501,0.01081701,0.0006131171,0.0001606416,0.9658164],"study_design_scores_gemma":[0.001123762,0.000496559,0.00006860263,0.000104516,0.00002375375,0.0002998681,0.0003471386,0.9850276,0.009877347,0.0004010548,0.001770859,0.0004589637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01860344,0.00006843758,0.9777068,0.0003974271,0.001891436,0.0008490884,0.00001578611,0.0004283024,0.00003928521],"genre_scores_gemma":[0.1930021,0.000005287443,0.8064657,0.0002302318,0.0001551928,0.00002910505,0.000003314293,0.00002631434,0.00008277968],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9664226,"threshold_uncertainty_score":0.999947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03540770120832357,"score_gpt":0.3343137645063191,"score_spread":0.2989060632979955,"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."}}