{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001140532,0.0003496849,0.0001341679,0.0001437345,0.0001097554,0.0001495076,0.0001887057,0.0002269882,0.001564974],"category_scores_gemma":[0.0001109694,0.000138163,0.0002153305,0.0001377247,0.0001906491,0.000283362,0.0002684155,0.0004127686,0.0004370704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001350378,"about_ca_system_score_gemma":0.0001562503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003023588,"about_ca_topic_score_gemma":0.0009835056,"domain_scores_codex":[0.9999135,0.000009146639,0.000006191311,0.00002044976,0.00002042358,0.00003033696],"domain_scores_gemma":[0.9999517,0.000009545293,0.00001555105,0.000007017174,0.00000871225,0.000007569457],"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":[0.00004063974,0.00002255575,0.0001114434,0.000187958,0.000008318357,0.0001209566,0.00004425582,0.0001710053,0.9946923,0.0005783797,0.0001029031,0.003919268],"study_design_scores_gemma":[0.000005469621,0.0001238914,0.0004369348,0.000005557828,0.000006624115,0.0001170948,0.00002034899,0.00021251,0.9951646,0.0000512321,0.003851368,0.000004350436],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693686,0.00417974,0.01569338,0.0002166828,0.0000711271,0.00009723072,0.0004002998,0.0001443823,0.009828438],"genre_scores_gemma":[0.9902859,0.002881888,0.004029543,0.00006122376,0.00001338816,0.00002760645,0.000165413,0.00001741578,0.002517679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001564974,"threshold_uncertainty_score":0.005235374,"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."}}