{"id":"W4407302797","doi":"10.1021/acscatal.4c06061","title":"Accessing Arenes via the Hydrodeoxygenation of Phenolic Derivatives Enabled by Hydrazine","year":2025,"lang":"en","type":"article","venue":"ACS Catalysis","topic":"Catalysis and Hydrodesulfurization Studies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Centre in Green Chemistry and Catalysis","funders":"NextGenerationEU; Natural Sciences and Engineering Research Council of Canada; Ministero dell’Istruzione, dell’Università e della Ricerca; McGill University; Fonds Québécois de la Recherche sur la Nature et les Technologies; Centre in Green Chemistry and Catalysis; Università degli Studi di Perugia; Canada Research Chairs","keywords":"Hydrodeoxygenation; Chemistry; Catalysis; Phenols; Hydrazine (antidepressant); Reagent; Organic chemistry; Lignin; Hydrazone; Combinatorial chemistry; Selectivity","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":[],"consensus_categories":[],"category_scores_codex":[0.0001417987,0.0001581865,0.0003027107,0.0001994173,0.0001816146,0.00005137042,0.0002448117,0.00006490907,0.00002061773],"category_scores_gemma":[0.00005974014,0.0001203789,0.00009564287,0.001272666,0.00008346866,0.0002125519,0.00008714711,0.00009662192,0.000008546291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003815423,"about_ca_system_score_gemma":0.00001152945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004275699,"about_ca_topic_score_gemma":0.00004665157,"domain_scores_codex":[0.9991062,0.00002235603,0.0003586505,0.0001789221,0.0001731509,0.0001607489],"domain_scores_gemma":[0.9993249,0.0001065296,0.00008873652,0.0003621823,0.00009821654,0.00001945131],"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":[0.00001004555,0.0001101096,0.004036149,0.0002324763,0.002244007,7.365228e-7,0.003106272,0.07017796,0.8729765,0.0004643341,0.008732675,0.03790867],"study_design_scores_gemma":[0.0003832067,0.000007509711,0.006481378,0.00005072678,0.0004527679,5.475902e-7,0.0004453297,0.03922217,0.9438672,0.0007565339,0.008043988,0.0002886465],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9237601,0.00589205,0.06369922,0.0006603994,0.0001311142,0.0001596276,0.00002720855,0.0001822873,0.005488009],"genre_scores_gemma":[0.9988039,0.0003441296,0.00006426626,0.00006927872,0.00002416298,0.00003743389,0.0001737011,0.00001649979,0.0004666109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07504383,"threshold_uncertainty_score":0.490891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006284240873989837,"score_gpt":0.2248655767107153,"score_spread":0.2185813358367254,"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."}}