{"id":"W2563955271","doi":"10.1016/j.bonr.2016.12.002","title":"Estimation of anisotropic permeability in trabecular bone based on microCT imaging and pore-scale fluid dynamics simulations","year":2016,"lang":"en","type":"article","venue":"Bone Reports","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Research Council; Canadian Institutes of Health Research","keywords":"Permeability (electromagnetism); Materials science; Representative elementary volume; Anisotropy; Fluid dynamics; Porosity; Tomography; Porous medium; Biomedical engineering; Matrix (chemical analysis); Mechanics; Mineralogy; Geology; Composite material; Chemistry; Optics; Physics; Microstructure","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":[0.0003890592,0.0004135752,0.0003729986,0.001363668,0.0002097673,0.0004096263,0.00035518,0.0005069739,0.0002539585],"category_scores_gemma":[0.001805655,0.0002965191,0.0003793249,0.0004563492,0.0005838255,0.0005290456,0.0004707463,0.0002518194,0.00008435943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003458615,"about_ca_system_score_gemma":0.0007306228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003726323,"about_ca_topic_score_gemma":0.003671982,"domain_scores_codex":[0.9997339,0.00003854493,0.00001540431,0.00003932435,0.0001511422,0.00002179336],"domain_scores_gemma":[0.9996074,0.0001768783,0.0000846446,0.00004472814,0.00006738108,0.00001909032],"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":[0.00007610027,0.00004979667,0.007595701,0.0001488816,0.00003971144,0.0002645379,0.0001659422,0.7143263,0.229715,0.007006943,0.0001825801,0.04042852],"study_design_scores_gemma":[0.000002781299,0.00001061358,0.001238792,0.00000541884,0.000005715974,0.00007701126,0.00001347102,0.984116,0.01354401,0.0007432177,0.0002321047,0.00001090571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.115797,0.0001485683,0.8827819,0.00003942381,0.000006968013,0.00004774883,0.00005901415,0.0003608498,0.0007585567],"genre_scores_gemma":[0.7055537,0.0002774372,0.2936133,0.00001531424,0.000006934185,0.00009882067,0.00009523169,0.00006810382,0.0002712124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003726323,"threshold_uncertainty_score":0.007409275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007149320915203334,"score_gpt":0.2810924331305955,"score_spread":0.2739431122153922,"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."}}