{"id":"W2081586698","doi":"10.1149/05801.0315ecst","title":"Investigation of Water Transport in Perforated Gas Diffusion Layer by Neutron Radiography","year":2013,"lang":"en","type":"article","venue":"ECS Transactions","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ford Motor Company (Canada)","funders":"National Institute of Standards and Technology; U.S. Department of Energy","keywords":"Neutron imaging; Water transport; Materials science; Gaseous diffusion; Proton exchange membrane fuel cell; Perforation; Diffusion; Membrane electrode assembly; Liquid water; Porosity; Layer (electronics); Electrode; Fuel cells; Bubble; Membrane; Composite material; Chemical engineering; Neutron; Chemistry; Water flow; Environmental science; Environmental engineering; Mechanics; Geology; Nuclear physics","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":[0.000050631,0.0001081905,0.0001459015,0.0001486218,0.00003323831,0.000009499144,0.0000471914,0.0001262097,0.0008775286],"category_scores_gemma":[1.682771e-7,0.00008456611,0.00005907732,0.0001877041,0.00003260503,0.0001693102,5.651281e-7,0.0001296961,0.00003400961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001544809,"about_ca_system_score_gemma":0.00000389453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002688825,"about_ca_topic_score_gemma":0.00002239326,"domain_scores_codex":[0.9993898,0.00001585284,0.0002577549,0.00009759414,0.00007197947,0.0001670602],"domain_scores_gemma":[0.9998152,0.000007122257,0.00001306371,0.00009209011,0.00002008045,0.00005246469],"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":[0.000003796319,0.00001914196,0.0005365773,0.0001399169,0.00001966967,5.312355e-7,0.0005844655,0.03911734,0.9593087,7.334267e-7,0.0002052616,0.00006385074],"study_design_scores_gemma":[0.0005618993,0.00003540831,0.00617485,0.00004409083,0.00003311197,0.000002078976,0.00005737831,0.01430507,0.9771004,0.0001063325,0.001407165,0.0001722539],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976373,0.0002431567,0.0007048359,0.0001054669,0.0002773523,0.000204131,0.00001645005,0.0001011395,0.0007101203],"genre_scores_gemma":[0.9988229,0.0008216121,0.0001217659,0.00000821598,0.00001086777,0.00003751151,0.00005718768,0.00002401434,0.00009587599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02481226,"threshold_uncertainty_score":0.9608322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006012618555531909,"score_gpt":0.1629021538621493,"score_spread":0.1568895353066175,"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."}}