{"id":"W4309837627","doi":"10.1149/ma2022-02391451mtgabs","title":"Probing Heterogeneous Water Distributions within Fuel Cell Membranes Using Combined Neutron and X-Ray Tomography (NeXT)","year":2022,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Neutron imaging; Proton exchange membrane fuel cell; Tomography; Neutron; Materials science; Membrane; Water transport; Fuel cells; Nuclear engineering; Environmental science; Water flow; Chemistry; Chemical engineering; Optics; Physics; Nuclear physics; Soil science","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":[0.000202609,0.0001753416,0.0001628258,0.00005083848,0.0009094159,0.0001502687,0.0001471415,0.00002065635,0.00007682066],"category_scores_gemma":[0.000001192792,0.0001659125,0.0000906532,0.0001397738,0.00004978208,0.0001053826,0.000177145,0.000262503,0.00001112931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000233758,"about_ca_system_score_gemma":0.00002582807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002917796,"about_ca_topic_score_gemma":0.000001711913,"domain_scores_codex":[0.9988737,0.0000469013,0.0002843064,0.0003121161,0.0001563809,0.0003265608],"domain_scores_gemma":[0.99945,0.00003930419,0.0001536682,0.000221339,0.00003570451,0.0001000295],"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":[0.00001692742,0.0004652587,0.001805923,0.00007525372,0.00006272873,0.00000457548,0.001500598,0.318743,0.6764605,0.0006917526,0.00006012721,0.0001133668],"study_design_scores_gemma":[0.004136557,0.0004854029,0.01033517,0.0001793813,0.000581683,0.00003426741,0.007752871,0.06115072,0.8410342,0.03741636,0.03395176,0.00294164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923552,0.00006242911,0.0000117513,0.0001355559,0.000112313,0.0002517856,0.00008369761,0.00005745378,0.006929798],"genre_scores_gemma":[0.9989482,0.000001003829,0.0005860298,0.00002350892,0.0001329337,0.00005735099,0.0001577895,0.00003536135,0.00005785476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2575923,"threshold_uncertainty_score":0.6994584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186183354359628,"score_gpt":0.2176397870712486,"score_spread":0.2057779535276524,"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."}}