{"id":"W2020130964","doi":"10.1016/j.jconhyd.2004.03.007","title":"Displacement and sweep efficiencies in a DNAPL recovery test using micellar and polymer solutions injected in a five-spot pattern","year":2004,"lang":"en","type":"article","venue":"Journal of Contaminant Hydrology","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental remediation; Dissolution; Flushing; Porous medium; Slug test; Volume (thermodynamics); Displacement (psychology); Sizing; Clogging; Chemistry; Chromatography; Porosity; Materials science; Environmental science; Soil water; Contamination; Soil science; Composite material; Hydraulic conductivity","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001388053,0.0005455956,0.0003258807,0.0005660307,0.0002968628,0.0004162314,0.0009037257,0.00117407,0.002612664],"category_scores_gemma":[0.001771179,0.0004225838,0.0002848559,0.0005501251,0.0006010606,0.0007246683,0.0003630569,0.0007065298,0.0007751602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004133494,"about_ca_system_score_gemma":0.0003619932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002134084,"about_ca_topic_score_gemma":0.002643255,"domain_scores_codex":[0.9988219,0.0002339016,0.0001052698,0.0002800816,0.0003037243,0.0002551174],"domain_scores_gemma":[0.9980239,0.001160994,0.000194324,0.0001786498,0.0002936299,0.0001485582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003192018,0.00008531915,0.0002654987,0.00003306355,0.000008831465,0.0000236603,0.00005918289,0.0002537118,0.996043,0.00009767635,0.00005055923,0.002760513],"study_design_scores_gemma":[0.00000795391,0.000250437,0.0004500211,0.000001597994,0.000006475691,0.00001845333,0.00001689766,0.0006117368,0.9984975,0.0000113966,0.000122843,0.000004659091],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768266,0.0004390635,0.01994787,0.0001896125,0.00004507055,0.00009287508,0.0002555058,0.0002653793,0.001938022],"genre_scores_gemma":[0.9560188,0.000519496,0.03138796,0.0002049073,0.00001605935,0.0001146894,0.0007256576,0.0001125325,0.01089991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002612664,"threshold_uncertainty_score":0.008740187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01002703740147056,"score_gpt":0.2174945179788007,"score_spread":0.2074674805773302,"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."}}