{"id":"W4403316747","doi":"10.1016/j.compfluid.2024.106450","title":"Error assessment of reconstructed 3D Digital Replica Models: From Computed Tomography data to pore-scale simulations","year":2024,"lang":"en","type":"article","venue":"Computers & Fluids","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Council Canada; Compute Canada","keywords":"Replica; Scale (ratio); Tomography; Computed tomography; Computer science; Statistical physics; Geometry; Algorithm; Mathematics; Physics; Optics; Radiology; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008180504,0.0002387854,0.0003298396,0.0003262779,0.0000349695,0.0001789145,0.0006699772,0.0001143871,0.00002804352],"category_scores_gemma":[0.000008216371,0.000262149,0.00008608033,0.0006842567,0.00005082582,0.0006943107,0.0003641194,0.0002261518,0.000006200316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007719985,"about_ca_system_score_gemma":0.0000433616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002280514,"about_ca_topic_score_gemma":0.00001026036,"domain_scores_codex":[0.9984934,0.00002028358,0.0004764642,0.0005450565,0.0002224195,0.0002423673],"domain_scores_gemma":[0.9983502,0.0002491505,0.00002648682,0.001183742,0.00006414385,0.0001262962],"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":[0.00001149731,0.00008825817,0.0006529157,0.0001912324,0.0005018594,0.00002770129,0.0003723025,0.7350735,0.01765688,0.0006545164,0.05170593,0.1930634],"study_design_scores_gemma":[0.0001025696,0.00005603219,0.0005907005,0.000298639,0.00002808071,0.000004688953,0.000008267727,0.9897969,0.001836753,0.001135622,0.005874079,0.0002676246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09689123,0.0003509923,0.8952363,0.00003645212,0.0008138717,0.0002817391,0.002499582,0.001946385,0.001943423],"genre_scores_gemma":[0.6961402,0.00001385991,0.3019006,0.00003697654,0.00008537793,0.0000094831,0.001754865,0.00005019221,0.000008456828],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.599249,"threshold_uncertainty_score":0.9999831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03354576945997481,"score_gpt":0.2885829813699329,"score_spread":0.2550372119099581,"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."}}