{"id":"W4286001779","doi":"10.3389/frwa.2022.935035","title":"Using Nano-XRM and High-Contrast Imaging to Inform Micro-Porosity Permeability During Stokes–Brinkman Single and Two-Phase Flow Simulations on Micro-CT Images","year":2022,"lang":"en","type":"article","venue":"Frontiers in Water","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Qatar Science and Technology Park; Qatar Petroleum; Energi Simulation","keywords":"Porosity; Microporous material; Permeability (electromagnetism); Materials science; Stokes flow; Porous medium; Mineralogy; Flow (mathematics); Composite material; Geology; Mechanics; Chemistry; Physics","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":[0.0003362779,0.0003244687,0.0002206526,0.0002262429,0.0002143001,0.0004609571,0.000563652,0.0007042103,0.0009009517],"category_scores_gemma":[0.0006923688,0.0002764901,0.0002872547,0.0001842193,0.0003857689,0.0004897875,0.0002604682,0.0004179159,0.00007592612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006219548,"about_ca_system_score_gemma":0.0007554103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004656082,"about_ca_topic_score_gemma":0.00515178,"domain_scores_codex":[0.9999403,0.000009444602,0.000003965637,0.00001419554,0.00002079475,0.00001135713],"domain_scores_gemma":[0.999779,0.0001160325,0.00003385272,0.00002768729,0.00002689483,0.00001648123],"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":[0.00006845182,0.00006865848,0.003077681,0.000113544,0.00002831455,0.0001990746,0.0001774887,0.8915525,0.09576125,0.00387219,0.0001593009,0.004921491],"study_design_scores_gemma":[0.000006757956,0.00001090983,0.0005665103,0.000002675069,0.000003146745,0.00001605651,0.00001074801,0.9881234,0.01074405,0.0003098299,0.0002011395,0.000004858821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8116579,0.0001453797,0.1834814,0.0002138466,0.00003029405,0.00008581772,0.0003547651,0.0006496322,0.003380854],"genre_scores_gemma":[0.9345359,0.0000941313,0.06420032,0.00004095518,0.000005394601,0.00008705781,0.0001473784,0.00008261362,0.0008062112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004656082,"threshold_uncertainty_score":0.009257972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007265972107072024,"score_gpt":0.2328533250155019,"score_spread":0.2255873529084299,"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."}}