{"id":"W4249944013","doi":"10.1149/ma2019-02/32/1410","title":"Insights into the Evolution of Chemical Degradation in Fuel Cell Membranes Using 4D in Situ Visualization","year":2019,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Membrane; Chemical imaging; Materials science; Degradation (telecommunications); Ionomer; Membrane electrode assembly; Chemical engineering; Polymer; Characterization (materials science); Composite material; Chemistry; Nanotechnology; Electrode; Electrolyte; Copolymer; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003616016,0.0005340732,0.0003117747,0.0007163669,0.0002570912,0.0008392979,0.0005373683,0.0007828458,0.00176996],"category_scores_gemma":[0.0002793529,0.0003658311,0.0002835726,0.0004040516,0.0005492393,0.0006801893,0.0005066615,0.0008678619,0.000323377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006422985,"about_ca_system_score_gemma":0.0002769405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009290304,"about_ca_topic_score_gemma":0.001169005,"domain_scores_codex":[0.9998241,0.00001409845,0.000009561987,0.00003793594,0.00008348871,0.000030866],"domain_scores_gemma":[0.9997543,0.00007081831,0.00008463806,0.00002857283,0.00004081101,0.00002098954],"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":[0.00001615799,0.00001257094,0.0003042261,0.0000736239,0.000003172974,0.0001182135,0.00007276075,0.0008007313,0.9958827,0.0003902198,0.00006945502,0.002256083],"study_design_scores_gemma":[0.000006597796,0.00005591118,0.002289565,0.00001538335,0.000007037417,0.0003448199,0.00008751015,0.01737821,0.9764224,0.0002064798,0.00316439,0.00002161969],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8811355,0.003907353,0.1043913,0.0004787336,0.0000811952,0.0001315289,0.001369792,0.001030703,0.007473995],"genre_scores_gemma":[0.8783102,0.003299515,0.1144721,0.0001385321,0.00005146814,0.0001392709,0.0005148206,0.0001777646,0.00289629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00176996,"threshold_uncertainty_score":0.005921125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007614661862583563,"score_gpt":0.2121703660556681,"score_spread":0.2045557041930846,"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."}}