{"id":"W4417118289","doi":"10.1002/cssc.202502031","title":"Formic Acid Pursues Efficient Hydrodeoxygenation of Naphthols and Phenolic Derivatives to Arenes","year":2025,"lang":"en","type":"article","venue":"ChemSusChem","topic":"Catalysis and Hydrodesulfurization Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre in Green Chemistry and Catalysis","funders":"Fonds de recherche du Québec – Nature et technologies; McGill University; Centre in Green Chemistry and Catalysis; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; European Commission; Università degli Studi di Perugia; Canada Research Chairs","keywords":"Hydrodeoxygenation; Formic acid; Hydrogen; Phenols; Lignin; Catalysis; Substrate (aquarium); Biofuel","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":[0.00007658143,0.0003042963,0.0001066748,0.0001553968,0.0001066912,0.0001532393,0.0001494054,0.0001720261,0.0007430958],"category_scores_gemma":[0.00007609754,0.00008583016,0.0001307156,0.0001339048,0.0001241851,0.0002089155,0.0001926102,0.0002382203,0.0002253852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001495314,"about_ca_system_score_gemma":0.0001602826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006371469,"about_ca_topic_score_gemma":0.0016717,"domain_scores_codex":[0.9999342,0.000006700756,0.000005265582,0.00001669464,0.00001781259,0.00001935193],"domain_scores_gemma":[0.9999712,0.000003865574,0.000009241709,0.000002920895,0.000006087112,0.00000670711],"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":[0.00003449938,0.00002835375,0.0001101603,0.00007898381,0.000004516229,0.00006827928,0.00001898396,0.0001490388,0.9959699,0.0002003704,0.00004380246,0.00329304],"study_design_scores_gemma":[0.000003241413,0.0000750155,0.0003750359,0.000003267004,0.000003222537,0.00004797092,0.00001063386,0.0003113288,0.9977522,0.00001631626,0.001399752,0.000001990267],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870983,0.001614802,0.005234775,0.0001091775,0.0000267816,0.00005314244,0.0001449303,0.00005347707,0.005664588],"genre_scores_gemma":[0.9954779,0.0009465559,0.002156968,0.00002305213,0.000005750346,0.00001369647,0.00008070062,0.00000813222,0.001287321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007430958,"threshold_uncertainty_score":0.002485871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006028598980709341,"score_gpt":0.2264202552494303,"score_spread":0.220391656268721,"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."}}