{"id":"W3025830500","doi":"10.1149/ma2020-01411809mtgabs","title":"Model Operational Matrix for the Betterment of Ruthenium As a Catalyst for the Electrochemical Nitrogen Reduction Reaction to Ammonia in Aqueous Electrolytes","year":2020,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Ammonia Synthesis and Nitrogen Reduction","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut National de la Recherche Scientifique","funders":"","keywords":"Ammonia production; Catalysis; Electrochemistry; Electrolysis; Ammonia; Electrocatalyst; Renewable energy; Chemistry; Electrochemical reduction of carbon dioxide; Aqueous solution; Electrolyte; Organic chemistry; Electrode; Carbon monoxide","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":[0.0003849307,0.0001702896,0.0001993437,0.00004323066,0.0001555388,0.000033537,0.0002029128,0.00009920295,0.000002416121],"category_scores_gemma":[0.0006253388,0.0001238926,0.0001397134,0.0001539167,0.00002503081,0.00007608601,0.00002496239,0.0002136529,0.000005829858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001323514,"about_ca_system_score_gemma":0.00007674986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001863031,"about_ca_topic_score_gemma":0.00001113695,"domain_scores_codex":[0.9987043,0.00001516032,0.0004530378,0.000290835,0.0002203398,0.0003163789],"domain_scores_gemma":[0.9990615,0.0004378376,0.0001579305,0.0001651798,0.0001023445,0.00007518549],"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":[0.0003740171,0.00003829003,0.00000739704,0.00003067174,0.00005918349,1.664615e-7,0.0003828042,0.1169409,0.8814269,0.00007708804,0.0001907871,0.0004717309],"study_design_scores_gemma":[0.0002370399,0.00006047098,0.00002176313,0.00002263974,0.00007306093,0.00001151704,0.0001513352,0.2149549,0.7837168,0.0002046207,0.0004396262,0.0001062165],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836785,0.0004449639,0.004746181,0.00989498,0.00007825388,0.0009742061,0.0000179876,0.00005683821,0.0001081415],"genre_scores_gemma":[0.9928136,0.000015526,0.005945389,0.0001160426,0.0005457617,0.0004536705,0.00003424519,0.00003894216,0.00003682145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09801394,"threshold_uncertainty_score":0.5052193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01676434069243685,"score_gpt":0.2526543377028118,"score_spread":0.2358899970103749,"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."}}