{"id":"W2075858322","doi":"10.1002/zamm.200510256","title":"Herschel-Bulkley diffusion filtering: non-Newtonian fluid mechanics in image processing","year":2006,"lang":"en","type":"article","venue":"ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Universität Innsbruck; Pacific Institute for the Mathematical Sciences","keywords":"Herschel–Bulkley fluid; Fluid mechanics; Non-Newtonian fluid; Mechanics; Newtonian fluid; Diffusion; Geology; Physics; Classical mechanics; Thermodynamics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001493731,0.0007628309,0.0006486656,0.000717541,0.0004918625,0.001286037,0.0007571948,0.002322217,0.0008120896],"category_scores_gemma":[0.003966337,0.0002986498,0.0006567718,0.0005891426,0.001790429,0.00205575,0.001077828,0.001287333,0.0002848412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001104711,"about_ca_system_score_gemma":0.0005661268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002728136,"about_ca_topic_score_gemma":0.00241576,"domain_scores_codex":[0.9996774,0.00009838803,0.00001789921,0.00007175541,0.00009825796,0.00003622701],"domain_scores_gemma":[0.9991221,0.0005545809,0.0001143816,0.00006548379,0.0001014683,0.00004198699],"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":[0.00009556032,0.00004662935,0.0007641534,0.0002354841,0.00004564115,0.000256507,0.0002410723,0.2761793,0.04353657,0.6403056,0.001350013,0.0369435],"study_design_scores_gemma":[0.000006286611,0.00001918194,0.0001874143,0.000008860024,0.000007438622,0.00003954364,0.00001245465,0.9063196,0.004475103,0.08760407,0.001306816,0.00001321274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02490634,0.001003924,0.9706735,0.0008303072,0.00006002703,0.00001644962,0.00003117388,0.00006395477,0.002414429],"genre_scores_gemma":[0.5381529,0.002668781,0.4439228,0.0004610475,0.0004995143,0.0001541355,0.0001424281,0.0002032566,0.01379512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002728136,"threshold_uncertainty_score":0.008015275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01173634464987547,"score_gpt":0.2610216563202244,"score_spread":0.2492853116703489,"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."}}