{"id":"W2809917666","doi":"10.14393/ufu.te.2017.6","title":"Study of catalysts for the hydrodeoxygenation reaction of phenol","year":2017,"lang":"en","type":"dissertation","venue":"","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Light Source; Basic Energy Sciences; Argonne National Laboratory; U.S. Department of Energy; National Energy Technology Laboratory; Office of Science; Companhia Brasileira de Metalurgia e Mineração; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Australian Government; Office of Fossil Energy; Fundação de Amparo à Pesquisa do Estado de Minas Gerais","keywords":"Hydrodeoxygenation; Catalysis; Phenol; Chemistry; Organic chemistry; Selectivity","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002309595,0.0002733644,0.0003874337,0.0003421995,0.0001593633,0.0004885745,0.0004674893,0.000280543,0.0006043942],"category_scores_gemma":[0.0003214963,0.0002052827,0.0003669401,0.0002051569,0.0001665351,0.000331655,0.0002815588,0.0003584964,0.0002263502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003158705,"about_ca_system_score_gemma":0.0001497161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009482789,"about_ca_topic_score_gemma":0.001475153,"domain_scores_codex":[0.9997419,0.0000280862,0.00002442922,0.00004847005,0.000110143,0.00004700738],"domain_scores_gemma":[0.9999137,0.0000257993,0.00001639558,0.000008337863,0.00002403824,0.0000116308],"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":[0.0002151912,0.00007961849,0.0007008101,0.0003734055,0.00004868531,0.0001201624,0.00005735404,0.0008675657,0.9892386,0.0004937002,0.00009750532,0.007707302],"study_design_scores_gemma":[0.00001886195,0.0004317203,0.00183414,0.00001493955,0.00003788785,0.0001059938,0.00004020421,0.003474879,0.9910145,0.00004706243,0.002972424,0.000007372094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992195,0.003616393,0.001844911,0.00004975052,0.0000243652,0.00003069516,0.0001207517,0.00003627943,0.002081851],"genre_scores_gemma":[0.9966742,0.001334228,0.001002222,0.000009069866,0.000008334272,0.00001107898,0.0001551436,0.00001239333,0.0007933309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009482789,"threshold_uncertainty_score":0.002291858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02223325448638931,"score_gpt":0.3101679360657278,"score_spread":0.2879346815793385,"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."}}