{"id":"W1971035943","doi":"10.1016/j.micromeso.2013.01.035","title":"Numerical simulation for tortuosity of porous media","year":2013,"lang":"en","type":"article","venue":"Microporous and Mesoporous Materials","topic":"Advanced Mathematical Modeling in Engineering","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Specialized Research Fund for the Doctoral Program of Higher Education of China; Ministry of Science and Technology of the People's Republic of China; National Natural Science Foundation of China","keywords":"Tortuosity; Homogenization (climate); Porous medium; Porosity; Permeability (electromagnetism); Representative elementary volume; Effective diffusion coefficient; Materials science; Mathematics; Mechanics; Physics; Chemistry; Composite material; Microstructure","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":[0.0002396486,0.0001729725,0.0003820056,0.00005211938,0.0000626914,0.00007784182,0.0002723855,0.00008306809,0.00003458612],"category_scores_gemma":[0.0001736771,0.0001503708,0.00003893618,0.00007113515,0.00004402342,0.0003187888,0.0001081041,0.0000389431,0.00000985931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000258296,"about_ca_system_score_gemma":0.00001878738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000069173,"about_ca_topic_score_gemma":5.17373e-7,"domain_scores_codex":[0.9987662,0.00002303266,0.0004910002,0.0003013638,0.0001405721,0.0002778501],"domain_scores_gemma":[0.9989813,0.0002682402,0.0001752284,0.0003318398,0.0001483304,0.00009503971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005635699,0.0003055288,0.00009034364,0.0008831162,0.00007499092,0.000009504919,0.002903954,0.02692023,0.8577184,0.05840636,0.0004287876,0.05220241],"study_design_scores_gemma":[0.002547695,0.0004483478,0.001387518,0.0001644351,0.00006111189,0.0001412855,0.000102078,0.2307095,0.6247571,0.1378132,0.0007234744,0.001144231],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3167628,0.000114582,0.6822774,0.00005894233,0.000242779,0.0004019167,0.000008339572,0.0001014348,0.0000317745],"genre_scores_gemma":[0.7828872,0.00001058498,0.2168896,0.00005314904,0.00006171923,0.00004902065,0.000006313266,0.00001761085,0.00002473921],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4661244,"threshold_uncertainty_score":0.6131942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01513581821557136,"score_gpt":0.2474647523576631,"score_spread":0.2323289341420918,"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."}}