{"id":"W2790712094","doi":"10.1149/ma2018-01/29/1716","title":"Understanding and Designing Oxygen Reduction/Evolution Reaction (ORR/OER) Catalysts By Combining Experimental and Ab-Initio Studies","year":2018,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Overpotential; Oxygen evolution; Catalysis; Electrochemical energy conversion; Electrochemistry; Water splitting; Density functional theory; Materials science; Nanotechnology; Chemistry; Chemical engineering; Electrode; Computational chemistry; Physical chemistry; Organic chemistry; Photocatalysis; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006087829,0.0009706116,0.0009681858,0.0006760268,0.0006334022,0.0006711937,0.001985725,0.00144979,0.001908616],"category_scores_gemma":[0.0006845252,0.0006201846,0.0006202949,0.0008177391,0.0008910223,0.0019264,0.000486225,0.001609496,0.0005117428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006276045,"about_ca_system_score_gemma":0.0006360324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001892245,"about_ca_topic_score_gemma":0.001953419,"domain_scores_codex":[0.9996728,0.00004976832,0.00001902189,0.00004692373,0.0001801846,0.00003131906],"domain_scores_gemma":[0.9997817,0.0001192237,0.00002527978,0.00003321945,0.00003316867,0.000007455335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001893589,0.0006360866,0.002966421,0.01094912,0.0001843688,0.000532694,0.0003664977,0.5212327,0.120918,0.2259434,0.003628085,0.1124532],"study_design_scores_gemma":[0.00005804397,0.0002435555,0.00114339,0.0004210759,0.00007180603,0.0001458906,0.0001795211,0.8949063,0.03347614,0.0550096,0.01429431,0.00005035273],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5003943,0.1119671,0.3111932,0.00409078,0.000731759,0.0004564078,0.002340702,0.001316714,0.067509],"genre_scores_gemma":[0.8224752,0.05695952,0.1159091,0.0003764152,0.0002058463,0.0005681289,0.001415865,0.0002219742,0.001868094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001985725,"threshold_uncertainty_score":0.006385028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05103815160227616,"score_gpt":0.2710774231672791,"score_spread":0.220039271565003,"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."}}