{"id":"W70046263","doi":"10.1007/978-3-540-30125-7_17","title":"A New Numerical Scheme for Anisotropic Diffusion","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","funders":"","keywords":"Smoothing; Computer science; Diffusion; Anisotropic diffusion; Algorithm; Scheme (mathematics); Diffusion process; Process (computing); Mathematical optimization; Artificial intelligence; Mathematics; Mathematical analysis; Computer vision; Physics; Innovation diffusion","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005983399,0.0005773627,0.0006975796,0.0006695827,0.000605733,0.0009809447,0.001471724,0.001289247,0.003882923],"category_scores_gemma":[0.001820429,0.0003776311,0.0006530686,0.0006510681,0.0008430291,0.001225754,0.00179125,0.001599046,0.001223925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005967836,"about_ca_system_score_gemma":0.00074713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002135226,"about_ca_topic_score_gemma":0.002855586,"domain_scores_codex":[0.9996665,0.00005953384,0.00002388373,0.00003856844,0.0001895422,0.00002198473],"domain_scores_gemma":[0.9995748,0.0001017655,0.00003438648,0.00009541719,0.0001472249,0.00004623324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002038857,0.0001508175,0.0004744952,0.0003116264,0.000076681,0.0001724601,0.0003199622,0.2153364,0.06972212,0.4689322,0.01124872,0.2330507],"study_design_scores_gemma":[0.00005240444,0.00003019583,0.00008438059,0.00001830953,0.00001409755,0.00009215467,0.00001063478,0.9458159,0.004221704,0.028893,0.02074213,0.00002509886],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003604457,0.0001808737,0.9911253,0.0001310414,0.000295684,0.00004892463,0.00004789588,0.0003140832,0.004251868],"genre_scores_gemma":[0.04741087,0.0002959457,0.9426719,0.000112117,0.0001029352,0.0001617872,0.0001163731,0.0003278051,0.008800201],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003882923,"threshold_uncertainty_score":0.01298964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01573356259726422,"score_gpt":0.2505225174823089,"score_spread":0.2347889548850446,"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."}}