{"id":"W2353422490","doi":"","title":"A KIND OF TRIGONOMETRIC GRNERATOR ON COMPUTING DYNAMIC EQUATIONS FASTLY","year":2003,"lang":"en","type":"article","venue":"","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Trigonometry; CORDIC; Computer science; Trigonometric functions; Computation; Computational science; Parallel computing; Algorithm; Throughput; Computer hardware; Field-programmable gate array; Mathematics; Operating system","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":[0.0004222837,0.00008422687,0.0001593505,0.0002417017,0.00006899307,0.00004746503,0.0003047422,0.00002694342,0.00003276694],"category_scores_gemma":[0.0003466758,0.00006618884,0.00006244919,0.001654335,0.00002195633,0.00009920783,0.00004726885,0.00008241731,0.00003144837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002530723,"about_ca_system_score_gemma":0.00003972142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008307001,"about_ca_topic_score_gemma":4.071493e-7,"domain_scores_codex":[0.9990467,0.000136424,0.0002283237,0.00023579,0.0001756425,0.0001771634],"domain_scores_gemma":[0.9989403,0.0005634513,0.00008701201,0.0002833249,0.00005228324,0.00007362144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[8.63438e-7,0.0001493368,0.00008385522,0.000004971003,0.00001026324,0.000001350578,0.00007441333,0.0004914481,0.0009716462,0.5083609,0.00001806531,0.4898329],"study_design_scores_gemma":[0.000582004,0.00041733,0.002270418,0.00001891311,0.000006296073,0.00000473447,0.00004495604,0.9709857,0.006910499,0.01633621,0.002138102,0.0002848279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007292888,0.0000382448,0.9848171,0.0001282809,0.0002403728,0.00008083155,8.914961e-7,0.00005077821,0.007350573],"genre_scores_gemma":[0.4870577,0.000001026681,0.512692,0.000101265,0.0000069517,0.000001147817,1.828771e-7,0.000002829963,0.0001368951],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9704943,"threshold_uncertainty_score":0.2699103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02732572413722066,"score_gpt":0.3039896790424556,"score_spread":0.2766639549052349,"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."}}