{"id":"W2061274662","doi":"10.1016/j.fuel.2012.06.116","title":"CuZn/ZrO2 catalytic honeycombs for dimethyl ether steam reforming and autothermal reforming","year":2012,"lang":"en","type":"article","venue":"Fuel","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ministerio de Ciencia e Innovación; European Regional Development Fund; Institució Catalana de Recerca i Estudis Avançats; Ministerio de Economía y Competitividad; Mountain Equipment Co-operative","keywords":"Catalysis; Methane reformer; X-ray photoelectron spectroscopy; Steam reforming; Dimethyl ether; Methane; Chemical engineering; Materials science; Yield (engineering); Fourier transform infrared spectroscopy; Nuclear chemistry; Chemistry; Hydrogen production; Organic chemistry; Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006862505,0.000330486,0.0004208558,0.000161204,0.0001258732,0.0000168612,0.0002372422,0.000224372,0.00004018925],"category_scores_gemma":[0.0002543259,0.0002732031,0.0001705994,0.0002002463,0.00006257961,0.0007467112,0.00019664,0.0003231366,0.00007141015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002735725,"about_ca_system_score_gemma":0.0000312152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002186699,"about_ca_topic_score_gemma":0.00001109376,"domain_scores_codex":[0.9980596,0.00001564361,0.0004336901,0.0003252865,0.0002553307,0.000910482],"domain_scores_gemma":[0.9988612,0.0001719885,0.0001427773,0.0004749894,0.00004482016,0.0003042521],"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":[0.0001800313,0.0002103872,0.00242381,0.001942326,0.0003932385,0.000009226464,0.009749514,0.0000767451,0.8595417,0.003814519,0.0001274479,0.1215311],"study_design_scores_gemma":[0.003257375,0.0001467215,0.001133621,0.000405183,0.0003295431,0.0003042716,0.001946128,0.007034058,0.8661769,0.0006423575,0.1169046,0.001719174],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828337,0.004236323,0.002246967,0.0001074906,0.000738711,0.0005774733,0.00004320471,0.0004380149,0.008778123],"genre_scores_gemma":[0.9918357,0.0000252521,0.002120975,0.00008512457,0.0007371228,0.00009151239,0.00005425003,0.00015047,0.004899646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1198119,"threshold_uncertainty_score":0.999972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01840983311365082,"score_gpt":0.2627959344339861,"score_spread":0.2443861013203353,"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."}}