{"id":"W2911722066","doi":"10.1039/c8em00565f","title":"Modelling permeation passive sampling: intra-particle resistance to mass transfer and comprehensive sensitivity analysis","year":2019,"lang":"en","type":"article","venue":"Environmental Science Processes & Impacts","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mass transfer; Adsorption; Permeation; Porosity; Microporous material; Sorbent; Thermal diffusivity; Sorption; Materials science; Particle (ecology); Mass transfer coefficient; Analyte; Particle size; Chemical engineering; Membrane; Chromatography; Chemistry; Composite material; Thermodynamics; Organic chemistry","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":[0.00300289,0.001658286,0.001279999,0.0009494966,0.0003108573,0.001218195,0.001085855,0.001811329,0.0007160283],"category_scores_gemma":[0.005628448,0.0006698566,0.002279571,0.0007011964,0.0006662497,0.001207681,0.001021195,0.00136356,0.0001552488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001045848,"about_ca_system_score_gemma":0.0008356901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006199764,"about_ca_topic_score_gemma":0.001804749,"domain_scores_codex":[0.9987757,0.0006091042,0.00005718685,0.0001832435,0.0002607314,0.0001140502],"domain_scores_gemma":[0.9963608,0.003025162,0.0002206169,0.0001470782,0.0002262063,0.00002015361],"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":[0.00002556315,0.00002834338,0.000545888,0.00009916021,0.0000504039,0.00006763951,0.00003444224,0.9912969,0.003719102,0.001516368,0.00005889499,0.00255736],"study_design_scores_gemma":[0.000002520453,0.00002791416,0.0002284204,0.000005189217,0.00001273269,0.00001857026,0.000007217684,0.9972891,0.001466703,0.0007745058,0.0001588849,0.00000826688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1797546,0.001043823,0.8131827,0.0003120782,0.00003432739,0.0003817338,0.0004933481,0.0003293908,0.004468],"genre_scores_gemma":[0.9558372,0.0007562869,0.0398539,0.00007783137,0.00002117106,0.0006593521,0.0003109816,0.0000715983,0.002411593],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006199764,"threshold_uncertainty_score":0.015881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499590393131866,"score_gpt":0.2334539015340314,"score_spread":0.2184579976027128,"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."}}