{"id":"W2341796638","doi":"10.1049/iet-cdt.2015.0058","title":"Decimal floating‐point fused multiply‐add with redundant internal encodings","year":2015,"lang":"en","type":"article","venue":"IET Computers & Digital Techniques","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; University of Saskatchewan","keywords":"Rounding; Adder; Arithmetic; Decimal; Critical path method; Computer science; Floating point; Square root; Binary number; Division (mathematics); Parallel computing; Multiplier (economics); Multiplication algorithm; Algorithm; Mathematics; Engineering; Latency (audio)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002368452,0.0006581004,0.000420926,0.0008996816,0.000433862,0.0008768343,0.0009342831,0.0003539466,0.003672069],"category_scores_gemma":[0.0006937251,0.0002885767,0.0005203965,0.000820618,0.0002959865,0.001011999,0.0004443698,0.0004979674,0.001619333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004491157,"about_ca_system_score_gemma":0.000626952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005379376,"about_ca_topic_score_gemma":0.001120337,"domain_scores_codex":[0.9996656,0.0000365748,0.00003751542,0.000057722,0.0001530922,0.00004936461],"domain_scores_gemma":[0.9996327,0.00005533176,0.00006324204,0.00009879647,0.0001357452,0.00001412339],"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":[0.0007427023,0.0001567647,0.001165401,0.0007498515,0.0001120022,0.0008851627,0.0002980181,0.03035175,0.2489045,0.0701834,0.008868823,0.6375817],"study_design_scores_gemma":[0.0001401176,0.001363506,0.002075165,0.0002411745,0.0002975049,0.003524635,0.0001267913,0.2827412,0.5653965,0.01995223,0.1240022,0.0001388933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1476938,0.002202337,0.8105761,0.0003958613,0.0005503546,0.0001413349,0.000372883,0.005449246,0.03261818],"genre_scores_gemma":[0.5750083,0.0008261665,0.4087049,0.0002187286,0.0001606437,0.0001182715,0.0005592834,0.0001335828,0.01427003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003672069,"threshold_uncertainty_score":0.01228428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259920138639028,"score_gpt":0.2639737822558015,"score_spread":0.2413745808694112,"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."}}