{"id":"W4399654213","doi":"10.1016/j.apcato.2024.206965","title":"Boosting light-driven hydrogen evolution through cerium vanadate/cerium sulphide type–II heterostructure","year":2024,"lang":"en","type":"article","venue":"Applied Catalysis O Open","topic":"Advanced Photocatalysis Techniques","field":"Energy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"King Saud University; Korea Institute of Energy Technology Evaluation and Planning; Jain University","keywords":"Cerium; Boosting (machine learning); Vanadate; Materials science; Heterojunction; Optoelectronics; Chemical engineering; Inorganic chemistry; Chemistry; Metallurgy; Computer science; Engineering; Artificial intelligence","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":[0.0001117367,0.0003069174,0.0002135012,0.000195914,0.0001287703,0.0003280978,0.0004466629,0.0003764207,0.0004050383],"category_scores_gemma":[0.0001210084,0.0002393178,0.0002493787,0.0001730171,0.0001495272,0.0002544308,0.0001953112,0.000276352,0.0002181518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002943032,"about_ca_system_score_gemma":0.0001879739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006979852,"about_ca_topic_score_gemma":0.002098514,"domain_scores_codex":[0.9999245,0.000005792593,0.000006265878,0.00002040381,0.00002442133,0.00001847652],"domain_scores_gemma":[0.9999288,0.000008457549,0.00001621738,0.000007378417,0.00002515152,0.00001393149],"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":[0.00001000879,0.000004107944,0.00005111505,0.00002564233,0.000003992766,0.0000287475,0.000005790401,0.00007172376,0.9992412,0.00008377621,0.00002793575,0.0004459293],"study_design_scores_gemma":[0.00000425663,0.00003841072,0.0003111457,0.000002566931,0.000006848165,0.00005881815,0.000007444936,0.001385391,0.9974354,0.00001610124,0.0007303592,0.00000319364],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868863,0.001083866,0.008811275,0.00009401677,0.00009070039,0.0000292645,0.0001904059,0.000182391,0.002631866],"genre_scores_gemma":[0.9904413,0.0005623375,0.00706953,0.00003262175,0.00000808701,0.00001922731,0.000160891,0.0000225289,0.001683417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006979852,"threshold_uncertainty_score":0.002135277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01596381965662649,"score_gpt":0.2804007122416093,"score_spread":0.2644368925849829,"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."}}