{"id":"W3018312834","doi":"10.1016/j.cageo.2020.104505","title":"Modeling transport of charged species in pore networks: Solution of the Nernst–Planck equations coupled with fluid flow and charge conservation equations","year":2020,"lang":"en","type":"article","venue":"Computers & Geosciences","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Waterloo","funders":"Canarie","keywords":"Nernst equation; Planck; Flow (mathematics); Charge (physics); Charge conservation; Fluid dynamics; Physics; Mechanics; Conservation law; Classical mechanics; Quantum mechanics; Electrode","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":[],"consensus_categories":[],"category_scores_codex":[0.0001753944,0.000096798,0.0001701249,0.00006710886,0.00006700796,0.00001244549,0.0001785491,0.00003864168,0.000004042126],"category_scores_gemma":[0.00002830064,0.00007652455,0.00002832964,0.0004823545,0.0001360776,0.0002384778,0.000018376,0.0000886252,1.57345e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002098214,"about_ca_system_score_gemma":0.00003959848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008093109,"about_ca_topic_score_gemma":0.0002474893,"domain_scores_codex":[0.9992239,0.00001902652,0.0002773656,0.0001482894,0.0001912049,0.0001402254],"domain_scores_gemma":[0.9996686,0.00007427727,0.00006353552,0.0001028262,0.00005874018,0.00003200839],"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":[0.000006046019,0.00001041451,0.003304575,0.00004423604,0.000006697451,3.243148e-7,0.00111454,0.9869753,0.006941251,0.0007766759,0.00002149479,0.0007985127],"study_design_scores_gemma":[0.0001406945,0.00004466722,0.003129577,0.0001193446,0.000008023421,4.851585e-7,0.00007595783,0.9950738,0.001219616,0.00009361627,0.00001113477,0.00008311405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3115902,0.0001146691,0.6876578,0.000248439,0.0001117526,0.0001535142,0.00001060901,0.00006001623,0.00005306341],"genre_scores_gemma":[0.9905148,0.00008701874,0.009265682,0.00006027039,0.00002566034,0.00001205888,0.00002328347,0.000007047584,0.00000414958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6789247,"threshold_uncertainty_score":0.312058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02331861220396944,"score_gpt":0.2023612407787191,"score_spread":0.1790426285747496,"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."}}