{"id":"W4405836307","doi":"10.1039/d4ma01262c","title":"Facile tailoring of a multi-element nanocomposite for electrocatalysis","year":2024,"lang":"en","type":"article","venue":"Materials Advances","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada First Research Excellence Fund; Innovation, Science and Economic Development Canada","keywords":"Electrocatalyst; Nanocomposite; Element (criminal law); Materials science; Nanotechnology; Composite material; Chemistry; Electrochemistry; Electrode; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001115442,0.0003555843,0.0001601303,0.0002285002,0.0001446239,0.0003274207,0.0002809222,0.0003083977,0.001181028],"category_scores_gemma":[0.0002048359,0.0002178105,0.0001219907,0.0001548527,0.0001382279,0.0003258469,0.0002420022,0.0004767226,0.0004452377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002011573,"about_ca_system_score_gemma":0.0001223499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001933886,"about_ca_topic_score_gemma":0.000987997,"domain_scores_codex":[0.9999124,0.000007098513,0.000007012001,0.00002685592,0.00003343038,0.00001329753],"domain_scores_gemma":[0.9999396,0.00001390427,0.00001186716,0.000007639442,0.00001528546,0.00001166539],"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":[0.00002812019,0.00002545747,0.00004636997,0.00003470884,0.00000411677,0.00001990166,0.000008558175,0.0001354357,0.9970047,0.000225919,0.00007883052,0.002387816],"study_design_scores_gemma":[0.000004757646,0.00004824986,0.0001817005,0.00000215434,0.000004945037,0.0000372989,0.000004575523,0.001359111,0.9964747,0.00003103849,0.001848324,0.000003082622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9436834,0.001599502,0.03877914,0.000257722,0.0001577177,0.000115948,0.0003180048,0.001005642,0.01408288],"genre_scores_gemma":[0.985086,0.0003392123,0.01115878,0.00004872786,0.000009639871,0.00004314394,0.0001386026,0.0001019777,0.003073995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001181028,"threshold_uncertainty_score":0.003950953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163628098297915,"score_gpt":0.260217369165703,"score_spread":0.2485810881827239,"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."}}