{"id":"W3158271463","doi":"10.1109/iscas51556.2021.9401213","title":"Efficient Multiple-Precision Posit Multiplier","year":2021,"lang":"en","type":"article","venue":"","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Multiplier (economics); Computer science; Computation; Architecture; Computer architecture; Parallel computing; Computer engineering; Algorithm","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":[0.0002063824,0.00009797523,0.0001322542,0.00003415948,0.00009391354,0.0001247137,0.0004136548,0.00004040408,0.00009406479],"category_scores_gemma":[0.0002236818,0.0000740872,0.00008320162,0.0004363482,0.0000171406,0.00005798331,0.0004492828,0.00009459761,0.0002114957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001970144,"about_ca_system_score_gemma":0.00003027408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001187255,"about_ca_topic_score_gemma":0.000001058908,"domain_scores_codex":[0.9988263,0.00009747894,0.000166008,0.0004131811,0.0002618967,0.0002351151],"domain_scores_gemma":[0.9988322,0.0003707227,0.00002862225,0.0005323761,0.0001053571,0.0001307712],"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":[0.000002582344,0.0001953034,0.0003082976,0.000003160998,0.00000841907,0.00007637909,0.0001203489,0.001259736,0.02413514,0.014689,0.0002973153,0.9589043],"study_design_scores_gemma":[0.0003436225,0.00002843578,0.003487629,0.000009515584,0.000001952132,0.00002431702,0.00001847312,0.9386462,0.04723609,0.001576055,0.008462681,0.0001650196],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00944668,0.0001126756,0.9837202,0.0009273286,0.0005873866,0.00005993894,7.71929e-7,0.0001460538,0.004998918],"genre_scores_gemma":[0.1334429,0.000003547908,0.864563,0.0005650909,0.00004954083,0.000004297826,5.703021e-7,0.00000523201,0.001365733],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9587393,"threshold_uncertainty_score":0.3021188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792319403482234,"score_gpt":0.2786333033509349,"score_spread":0.2607101093161126,"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."}}