{"id":"W2289301188","doi":"10.82308/24033","title":"Data conversion in residue number system","year":2011,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Kuwait University; McGill University","keywords":"Residue number system; Computer science; Data conversion; Converters; Binary number; Electronic circuit; Arithmetic; Electronic engineering; Computer engineering; Power (physics); Computer hardware; Algorithm; Mathematics; Engineering; Electrical 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001169124,0.0005037956,0.0005049688,0.0003066436,0.0002937482,0.00004087765,0.001451419,0.0003858254,0.0004611464],"category_scores_gemma":[0.0001103166,0.0005339572,0.00008409131,0.000753288,0.0000643828,0.002185628,0.0004833949,0.000913901,0.003758918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007919561,"about_ca_system_score_gemma":0.00001983537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004407208,"about_ca_topic_score_gemma":0.0002961556,"domain_scores_codex":[0.9969209,0.0001843579,0.0007391946,0.00079125,0.0005157327,0.0008486046],"domain_scores_gemma":[0.9975093,0.0001046886,0.0001075875,0.001899805,0.00008745856,0.0002911448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001546828,0.001847264,0.05979153,0.01060613,0.001926715,0.00654528,0.0003816486,0.005168665,0.2101934,0.5653167,0.002887338,0.1337885],"study_design_scores_gemma":[0.00983244,0.000377303,0.03955554,0.002822442,0.000410397,0.0007633878,0.001282638,0.03787541,0.6929837,0.003205622,0.2044287,0.006462327],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8622639,0.00009882571,0.000006005512,0.000003404866,0.001315491,0.0004374329,0.0006522207,0.001077069,0.1341456],"genre_scores_gemma":[0.9969067,0.00009182576,0.002187068,0.0000594356,0.00004135781,0.00004156807,0.00009949186,0.0001771428,0.0003954213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5621111,"threshold_uncertainty_score":0.9997112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03581885678108765,"score_gpt":0.2132756919869956,"score_spread":0.177456835205908,"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."}}