{"id":"W2544911497","doi":"10.1016/j.advwatres.2016.10.023","title":"Construction of pore network models for Berea and Fontainebleau sandstones using non-linear programing and optimization techniques","year":2016,"lang":"en","type":"article","venue":"Advances in Water Resources","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Relative permeability; Percolation (cognitive psychology); Porosity; Nonlinear system; Permeability (electromagnetism); Porous medium; Geology; Mechanics; Flow (mathematics); Capillary action; Materials science; Geotechnical engineering; Computer science; Algorithm; Physics; Chemistry; Composite material","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":[0.0002844963,0.0004693493,0.0007466457,0.0005911618,0.000599904,0.0009022429,0.001047703,0.00129243,0.001968096],"category_scores_gemma":[0.001235748,0.0007256935,0.0007837218,0.0004940901,0.0006452669,0.0005970271,0.0006009988,0.0006897062,0.0002665684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00112662,"about_ca_system_score_gemma":0.002002194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02952908,"about_ca_topic_score_gemma":0.03485228,"domain_scores_codex":[0.9998913,0.00002647432,0.000007099515,0.00002597881,0.00003162258,0.000017465],"domain_scores_gemma":[0.9995072,0.0003119053,0.00004939508,0.0000339156,0.00006567685,0.00003194244],"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":[0.000004694921,0.000008915353,0.0002148615,0.000008992383,0.000002642176,0.00001362019,0.000005971288,0.9969591,0.0002831204,0.001365142,0.00004950795,0.001083464],"study_design_scores_gemma":[0.000001563501,0.000001529486,0.00003866907,9.206645e-7,6.812876e-7,0.000001747538,0.000003209582,0.9993598,0.0001073185,0.0004072718,0.00007627317,0.000001069358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3788526,0.0002329584,0.6012217,0.0004370242,0.00004575428,0.0001782419,0.001644897,0.001108196,0.01627861],"genre_scores_gemma":[0.8766472,0.0001496475,0.1171524,0.0000366655,0.00001088483,0.0002364844,0.0007511088,0.0002311744,0.004784443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02952908,"threshold_uncertainty_score":0.05871445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007409475852811597,"score_gpt":0.2398457565221469,"score_spread":0.2324362806693353,"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."}}