{"id":"W2086619515","doi":"10.1016/j.apcata.2008.01.021","title":"Application of multi-walled carbon nanotubes as efficient support to NiMo hydrotreating catalyst","year":2008,"lang":"en","type":"article","venue":"Applied Catalysis A General","topic":"Catalysis and Hydrodesulfurization Studies","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":false,"ca_institutions":"Syncrude (Canada); University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Hydrodesulfurization; Catalysis; Materials science; Carbon nanotube; Chemical engineering; Hydrodenitrogenation; Naphtha; Ferrocene; Adsorption; Dispersion (optics); Temperature-programmed reduction; Raman spectroscopy; Calcination; Sulfidation; Metallurgy; Chemistry; Metal; Nanotechnology; Electrochemistry; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001623737,0.0003398874,0.0006586688,0.0003448067,0.0001817568,0.00001773786,0.0002689516,0.00009737605,0.00002220509],"category_scores_gemma":[0.0000230124,0.0003424475,0.0002000221,0.001016344,0.00008049143,0.00003366205,0.0001299343,0.000099031,0.0001401481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001169709,"about_ca_system_score_gemma":0.00003275496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005177603,"about_ca_topic_score_gemma":0.0001352398,"domain_scores_codex":[0.99796,0.0000119188,0.0007056916,0.0005027726,0.0004382127,0.000381457],"domain_scores_gemma":[0.9989037,0.00003532545,0.0001267326,0.0006689052,0.000109765,0.0001555645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002148186,0.0001632194,0.001065178,0.00004944224,0.0004271073,0.000006334178,0.003052769,0.5265833,0.4653682,0.0002587079,0.0002676166,0.002736754],"study_design_scores_gemma":[0.001221216,0.00004631956,0.002142784,0.00001095727,0.0003806672,0.00002719477,0.0003357689,0.2549136,0.7378246,0.00001325994,0.002263105,0.0008205136],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984706,0.0002037877,0.007626547,0.0000247883,0.00006841873,0.0004928981,0.00002654169,0.0002517099,0.006599248],"genre_scores_gemma":[0.9970325,0.00005337724,0.001439208,0.00004932095,0.0001211978,0.0004427565,0.0004284115,0.00006674524,0.0003664612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2724565,"threshold_uncertainty_score":0.9999027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009416578873912,"score_gpt":0.2194032160243097,"score_spread":0.2093090502355706,"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."}}