{"id":"W2006827615","doi":"10.1098/rspa.2006.1704","title":"On the size of representative volume element for Darcy law in random media","year":2006,"lang":"en","type":"article","venue":"Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences","topic":"Composite Material Mechanics","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Representative elementary volume; Darcy's law; Random field; Scaling; Porous medium; Statistical physics; Mathematics; Mathematical analysis; Finite element method; Physics; Materials science; Geometry; Statistics; Porosity; Thermodynamics","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":[0.002262953,0.0003550909,0.0005218934,0.001242312,0.0005423977,0.001537192,0.0009137086,0.0008481483,0.001615453],"category_scores_gemma":[0.01520308,0.0003908437,0.0004067375,0.0003623356,0.00314847,0.003304861,0.001115457,0.001004359,0.0001826691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007524377,"about_ca_system_score_gemma":0.0004437302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006033036,"about_ca_topic_score_gemma":0.0003498276,"domain_scores_codex":[0.9992587,0.000283655,0.00002981709,0.0001595982,0.0001949614,0.00007325548],"domain_scores_gemma":[0.9887001,0.008579711,0.0007917134,0.000702804,0.0006477634,0.0005779167],"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":[0.00007822974,0.00004823981,0.002228027,0.0001918634,0.00001514817,0.0001946983,0.0004988173,0.05727641,0.02126269,0.9036294,0.0008717272,0.01370483],"study_design_scores_gemma":[0.00001887769,0.00009714255,0.001786008,0.00005393633,0.00001484802,0.0002217848,0.00009120216,0.7063627,0.00728525,0.2813592,0.002667987,0.00004117285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2882829,0.003091254,0.6888137,0.001208481,0.0001190054,0.00008386919,0.00009090016,0.0004955493,0.01781425],"genre_scores_gemma":[0.9327322,0.0009624342,0.0641548,0.0001247032,0.0001516598,0.0001397862,0.00007445229,0.0001634771,0.001496549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002262953,"threshold_uncertainty_score":0.01196778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007148353613298821,"score_gpt":0.205221519410157,"score_spread":0.1980731657968581,"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."}}