{"id":"W2338498037","doi":"10.1149/ma2015-01/28/1650","title":"(Invited) Imaging and Quantitative Chemical Mapping of PEM-FC Catalyst Layers By Scanning Transmission X-Ray Microscopy","year":2015,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Proton exchange membrane fuel cell; Materials science; Microscopy; Cathode; Electrolyte; Transmission electron microscopy; Nanotechnology; Chemical engineering; Electrode; Fuel cells; Chemistry; Optics; Physics","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":[0.0001732753,0.0004605365,0.0002058189,0.0008341343,0.0002293225,0.0006114694,0.0004852289,0.0007565049,0.009392626],"category_scores_gemma":[0.0001932274,0.0002828079,0.0002084802,0.000365848,0.0002278038,0.000576526,0.0004009402,0.0007196828,0.004803183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003177298,"about_ca_system_score_gemma":0.0002051496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009219324,"about_ca_topic_score_gemma":0.001534529,"domain_scores_codex":[0.9998531,0.000007264438,0.000006616529,0.00003481624,0.00008370305,0.00001439848],"domain_scores_gemma":[0.9998821,0.00001559159,0.000015553,0.00002656381,0.00004975682,0.00001049637],"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":[0.00003276549,0.000007380526,0.0001861015,0.0001474664,0.00000395033,0.00009382258,0.00002652805,0.000295413,0.9785582,0.0005581669,0.002186186,0.01790392],"study_design_scores_gemma":[0.000010697,0.00007143858,0.004351846,0.00004792753,0.00001043084,0.0006149039,0.00005279082,0.005500318,0.937558,0.0004275928,0.0513374,0.00001666131],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3067093,0.01497624,0.5659305,0.002121594,0.001500247,0.0005221036,0.01020665,0.01814233,0.079891],"genre_scores_gemma":[0.4051755,0.01306644,0.5119029,0.001113956,0.0003223194,0.0005412327,0.005105747,0.001383175,0.06138882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009392626,"threshold_uncertainty_score":0.03142142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01867229137766322,"score_gpt":0.2845197776293567,"score_spread":0.2658474862516935,"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."}}