{"id":"W2065033939","doi":"10.1016/j.jmr.2008.07.011","title":"Spatial and temporal mapping of water content across Nafion membranes under wetting and drying conditions","year":2008,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Innovation Council; National Research Council Canada; University of New Brunswick","funders":"","keywords":"Nafion; Wetting; Water transport; Water content; Electrolyte; Image resolution; Membrane; Materials science; Temporal resolution; Analytical Chemistry (journal); Chemistry; Nuclear magnetic resonance; Optics; Composite material; Chromatography; Environmental science; Soil science; Water flow; Physics; Electrode","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001847732,0.00009150562,0.0002315311,0.00004503246,0.00008146605,0.00002040175,0.00004562478,0.00006439225,0.0000409278],"category_scores_gemma":[0.00001175764,0.00006440452,0.00003396924,0.00003076671,0.0001027266,0.00009840335,0.00002329402,0.000118009,9.693365e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001046645,"about_ca_system_score_gemma":0.000007106682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003081813,"about_ca_topic_score_gemma":0.000003130885,"domain_scores_codex":[0.9992291,0.00002090843,0.0004070732,0.00006569254,0.0001223273,0.0001549373],"domain_scores_gemma":[0.9997124,0.00003682609,0.00008975638,0.00005151663,0.00005986373,0.00004965412],"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":[0.0000716298,0.00003464802,0.00752195,0.00123611,0.0000504534,0.0001866958,0.004065742,0.00270222,0.9785522,0.00001499573,0.000211699,0.00535164],"study_design_scores_gemma":[0.01005467,0.001205598,0.3713742,0.003322661,0.0001500168,0.006865554,0.003604889,0.01744272,0.5416777,0.001128058,0.04201281,0.001161119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705471,0.02871929,0.00008674575,0.000101559,0.0002768355,0.00005736884,0.000005940618,0.000009812359,0.0001953005],"genre_scores_gemma":[0.9913259,0.007965614,0.0004820644,0.0000171735,0.00008594244,9.358656e-7,9.445041e-7,0.00001265912,0.000108801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4368745,"threshold_uncertainty_score":0.262634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02156299930141634,"score_gpt":0.2162046652771928,"score_spread":0.1946416659757765,"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."}}