{"id":"W2086037957","doi":"10.1016/j.apcata.2015.01.027","title":"Selectivity control of Cu promoted iron-based Fischer-Tropsch catalyst by tuning the oxidation state of Cu to mimic K","year":2015,"lang":"en","type":"article","venue":"Applied Catalysis A General","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Light Source (Canada)","funders":"Western Economic Diversification Canada; Natural Sciences and Engineering Research Council of Canada; University of Wyoming; Canadian Institutes of Health Research; University of Saskatchewan; National Research Council Canada; Canada Foundation for Innovation","keywords":"Syngas; Catalysis; Fischer–Tropsch process; Chemistry; Copper; Selectivity; XANES; Hydrocarbon; Inorganic chemistry; Oxidation state; Partial oxidation; Organic chemistry; Spectroscopy","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":[0.0001808007,0.0003364782,0.0002314255,0.0002426882,0.0002666347,0.0002429376,0.0005996447,0.00041786,0.001050216],"category_scores_gemma":[0.0001934255,0.000164636,0.0001551824,0.0001648152,0.0002244921,0.0003390916,0.0001876551,0.0003546249,0.0002824205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004620974,"about_ca_system_score_gemma":0.0002239049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00166182,"about_ca_topic_score_gemma":0.002910912,"domain_scores_codex":[0.9998448,0.00001357379,0.00001157393,0.00004182793,0.00002955569,0.00005863394],"domain_scores_gemma":[0.9999529,0.000007949735,0.00001085053,0.000006925912,0.0000108511,0.00001052137],"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":[0.0004345116,0.00004717317,0.0002623721,0.0001131199,0.00001153384,0.0001445106,0.00006906038,0.0003794265,0.992534,0.000887624,0.0004630578,0.004653586],"study_design_scores_gemma":[0.00001142188,0.00006472878,0.0002566449,0.000002319765,0.000005333839,0.00003803954,0.00001063215,0.001808555,0.9967819,0.00003315308,0.0009809112,0.000006387356],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928508,0.0005914213,0.002573291,0.0001392022,0.00004556273,0.00001770825,0.0001277606,0.0001407912,0.003513537],"genre_scores_gemma":[0.9984009,0.0001651093,0.0006449923,0.0000173905,0.000004733253,0.000005525907,0.00005720858,0.000009820256,0.0006943959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00166182,"threshold_uncertainty_score":0.003513277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01013057290722626,"score_gpt":0.2258118153551485,"score_spread":0.2156812424479223,"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."}}