{"id":"W4384930602","doi":"10.1021/acscatal.3c02024","title":"Nickel–Iron Bimetal as a Cost-Effective Cocatalyst for Light-Driven Hydrogen Release from Methanol and Water","year":2023,"lang":"en","type":"article","venue":"ACS Catalysis","topic":"Advanced Photocatalysis Techniques","field":"Energy","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Shanghai Jiao Tong University; Beijing Municipal Natural Science Foundation; Beijing Municipal Education Commission; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Bimetal; Hydrogen; Materials science; Water splitting; Catalysis; Hydrogen production; Chemical engineering; Nickel; Artificial photosynthesis; Nanotechnology; Inorganic chemistry; Photochemistry; Chemistry; Photocatalysis; Organic chemistry; Metallurgy","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":[0.00007957005,0.0002175498,0.0001267526,0.0001480547,0.0001191384,0.0001992215,0.0002768842,0.0002040229,0.0004834913],"category_scores_gemma":[0.00008708437,0.0001098049,0.0001229736,0.00009051081,0.0001086389,0.0001888967,0.0001625644,0.00020605,0.0002211406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002675501,"about_ca_system_score_gemma":0.0001263957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005418954,"about_ca_topic_score_gemma":0.001089756,"domain_scores_codex":[0.9999382,0.000007042743,0.000004527716,0.00001215526,0.00002596576,0.00001207739],"domain_scores_gemma":[0.9999804,0.000002170633,0.000004447445,0.000003419219,0.000004082271,0.000005458048],"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":[0.00005525151,0.00003819838,0.0001708548,0.00006127566,0.000007910501,0.00007410757,0.00001617031,0.000320513,0.9938571,0.0005203714,0.000187216,0.004691049],"study_design_scores_gemma":[0.000009349251,0.0001040756,0.0006610961,0.000002660001,0.00001081983,0.00006802708,0.00001409487,0.004867686,0.9917952,0.00005695084,0.002404396,0.000005565644],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877805,0.001109631,0.006780231,0.000154245,0.00004084892,0.00002828902,0.0001226191,0.0001834997,0.003800064],"genre_scores_gemma":[0.9947882,0.0002783043,0.003656024,0.00001503226,0.00000522561,0.00001271473,0.00007943669,0.00001230714,0.0011528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005418954,"threshold_uncertainty_score":0.001941204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.012946096293938,"score_gpt":0.2799897389343891,"score_spread":0.2670436426404511,"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."}}