{"id":"W1602459978","doi":"10.1016/j.cad.2012.10.023","title":"Linear methods for <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si20.gif\" display=\"inline\" overflow=\"scroll\"><mml:msup><mml:mrow><mml:mi>G</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math>, <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si21.gif\" display=\"inline\" overflow=\"scroll\"><mml:msup><mml:mrow><mml:mi>G</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math>, and <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si22.gif\" display=\"inline\" overflow=\"scroll\"><mml:msup><mml:mrow><mml:mi>G</mml:mi></mml:mrow><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msup></mml:math>—Multi-degree reduction of Bézier curves","year":2012,"lang":"lv","type":"article","venue":"Computer-Aided Design","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reduction (mathematics); Degree (music); Algorithm; Computer science; Linear equation; Scroll; Applied mathematics; Stability (learning theory); Mathematics; Geometry; Machine learning; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.008784277,0.005150056,0.002254501,0.00297659,0.006048894,0.005560411,0.009451112,0.01077775,0.3346302],"category_scores_gemma":[0.008318436,0.009597742,0.009393195,0.005786347,0.007290183,0.008325795,0.009309557,0.008216452,0.005728008],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001500684,"about_ca_system_score_gemma":0.005931685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004728385,"about_ca_topic_score_gemma":0.002290912,"domain_scores_codex":[0.9600806,0.002734993,0.009213433,0.008128127,0.009244937,0.01059788],"domain_scores_gemma":[0.9646105,0.008861762,0.00962635,0.01017099,0.001187331,0.005543076],"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":[0.006917644,0.001953849,0.00003030135,0.006329686,0.008471764,0.004329579,0.003978949,0.01376202,0.008614953,0.6348114,0.3033673,0.007432532],"study_design_scores_gemma":[0.005237571,0.004518958,0.0001211142,0.003821805,0.005812698,0.005357626,0.002284363,0.4158773,0.5413244,0.0001468984,0.01031582,0.005181408],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5772023,0.01036152,0.03922104,0.002188615,0.01301921,0.000459785,0.003503392,0.002549181,0.3514949],"genre_scores_gemma":[0.9022228,0.009107751,0.05248642,0.003682352,0.009762755,0.007628509,0.008865501,0.005156414,0.001087566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6346645,"threshold_uncertainty_score":0.9997038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02868845736425522,"score_gpt":0.2737595632898988,"score_spread":0.2450711059256435,"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."}}