{"id":"W2172455330","doi":"10.1007/978-3-642-10649-1_20","title":"A Discrete Approach to Multiresolution Curves and Surfaces","year":2009,"lang":"en","type":"book-chapter","venue":"Transactions on computational science","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Subdivision; Subdivision surface; Computer science; Biorthogonal wavelet; Multiresolution analysis; Biorthogonal system; Representation (politics); Constraint (computer-aided design); Simple (philosophy); Wavelet; Basis (linear algebra); Algorithm; Topology (electrical circuits); Theoretical computer science; Mathematics; Artificial intelligence; Wavelet transform; Geometry; Discrete wavelet transform","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":[0.0001091755,0.0002023445,0.0002002722,0.0002791044,0.0001965097,0.00003887169,0.0001784583,0.0000582377,0.0000169119],"category_scores_gemma":[0.000004854418,0.0001956334,0.00005700738,0.0002330628,0.000223711,0.0001873204,0.000004216877,0.0002104573,0.0000173352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001321865,"about_ca_system_score_gemma":0.00002631381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004791098,"about_ca_topic_score_gemma":0.00000284722,"domain_scores_codex":[0.9987976,0.000004785993,0.0001930492,0.0003636525,0.0004728648,0.0001680381],"domain_scores_gemma":[0.9995624,0.00005672014,0.00003211202,0.0001303208,0.00008094203,0.0001374931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002874562,0.00001229384,1.401008e-7,0.00002691792,0.00001121957,3.800997e-7,0.00002768048,0.9460849,0.00007112475,0.003802043,0.00007177606,0.04988864],"study_design_scores_gemma":[0.00009038253,0.000108065,0.0003415126,0.0003264243,0.00005202193,0.00001150612,0.000005401379,0.9691216,0.0001857229,0.02258288,0.006613788,0.0005606508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00003125389,0.0002754993,0.9355254,0.0001588105,0.00003001849,0.0002263313,0.00003535244,0.0003460314,0.06337129],"genre_scores_gemma":[0.5368271,0.001055111,0.4364248,0.0006337958,0.00005527157,0.0000583069,0.00005959787,0.00007612211,0.02480988],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5367959,"threshold_uncertainty_score":0.79777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01430688324273405,"score_gpt":0.2517694362526643,"score_spread":0.2374625530099302,"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."}}