{"id":"W1499669544","doi":"10.1109/mwscas.1997.662165","title":"Eisenstein residue number system with applications to DSP","year":2002,"lang":"en","type":"article","venue":"","topic":"Cryptography and Residue Arithmetic","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Residue number system; Digital signal processing; Computer science; Arithmetic; Radix (gastropod); Eisenstein integer; Quadratic equation; Residue (chemistry); Theoretical computer science; Mathematics; Algorithm; Computer hardware","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007196406,0.00009867675,0.0001021258,0.00008708203,0.0001488375,0.0001162926,0.0004887329,0.0000342906,0.00006659272],"category_scores_gemma":[0.0000020078,0.00006998764,0.00003853114,0.0009472004,0.00002823457,0.0001294701,0.00008880137,0.00006321803,0.001359343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001781922,"about_ca_system_score_gemma":0.000008486971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007491519,"about_ca_topic_score_gemma":0.00006914717,"domain_scores_codex":[0.9991006,0.00002623207,0.000129202,0.0003225018,0.0002050256,0.0002164974],"domain_scores_gemma":[0.9990616,0.00004160705,0.00002687391,0.0006642974,0.00005931436,0.0001463042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002296982,0.00007792636,0.001782142,0.00003175809,0.00002172112,0.00002502207,0.0003553545,0.0001664944,0.0001227859,0.97494,0.007815787,0.01465869],"study_design_scores_gemma":[0.005638799,0.001432086,0.06374392,0.0009030143,0.0001754383,0.003609629,0.00310019,0.1898205,0.03099109,0.008151405,0.6866522,0.005781776],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002448757,0.00004308206,0.8606578,0.001550318,0.00004151075,0.0003267802,9.433372e-7,0.0003822901,0.1345485],"genre_scores_gemma":[0.8550269,0.000003085881,0.1421988,0.0003218082,0.00004739132,0.0001091047,3.224644e-7,0.000007417053,0.00228521],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9667886,"threshold_uncertainty_score":0.9994182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01212865986160409,"score_gpt":0.2160689380021435,"score_spread":0.2039402781405394,"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."}}