{"id":"W3007827090","doi":"10.1002/celc.202000038","title":"Boosting the Oxygen Reduction Performance via Tuning the Synergy between Metal Core and Oxide Shell of Metal−Organic Frameworks‐Derived Co@CoO<sub>x</sub>","year":2020,"lang":"en","type":"article","venue":"ChemElectroChem","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Argonne National Laboratory; Office of Science; Canadian Light Source","keywords":"Imidazolate; Catalysis; Oxide; Metal; Materials science; Chemical engineering; Oxygen; Metal-organic framework; Chemistry; Inorganic chemistry; Physical chemistry; Organic chemistry; Adsorption; Metallurgy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004675887,0.0002245988,0.0001011188,0.00009769118,0.00007532503,0.0002085915,0.0001770886,0.0001648721,0.0005383452],"category_scores_gemma":[0.0001091288,0.00009217083,0.00008296326,0.00006666291,0.0001511589,0.0002070588,0.0001746119,0.0001791166,0.0001463283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001756642,"about_ca_system_score_gemma":0.00008605857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000378282,"about_ca_topic_score_gemma":0.0009309594,"domain_scores_codex":[0.9999591,0.000003252569,0.000001964312,0.00001000077,0.00001274809,0.00001299074],"domain_scores_gemma":[0.9999738,0.000005709489,0.000008684794,0.00000192681,0.000005047181,0.000004868351],"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":[0.00004660878,0.00001193071,0.0001344982,0.00003919351,0.000003845507,0.00002805009,0.000009583446,0.0002090302,0.9973752,0.0001317337,0.00005832458,0.001952096],"study_design_scores_gemma":[0.000006866576,0.00005615633,0.0006891545,0.000001798847,0.0000084691,0.00004543187,0.00001134474,0.003686579,0.994751,0.00002517891,0.0007147075,0.000003327068],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937333,0.0003990181,0.003841456,0.00004812314,0.00001523858,0.00001060485,0.00003679244,0.0001589869,0.00175639],"genre_scores_gemma":[0.9982976,0.0001139194,0.001158734,0.0000115064,0.000002011488,0.000004033626,0.00001480201,0.00001025793,0.0003871229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005383452,"threshold_uncertainty_score":0.001800954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0143764862418599,"score_gpt":0.2107744438501329,"score_spread":0.196397957608273,"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."}}