{"id":"W4402759824","doi":"10.1021/acsanm.4c03284","title":"Covalent Organic Framework-Templated <i>N</i>-Heterocyclic Carbene-Functionalized Gold Nanoparticles for the Catalytic Reduction of Nitrophenol","year":2024,"lang":"en","type":"article","venue":"ACS Applied Nano Materials","topic":"Covalent Organic Framework Applications","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Carbene; 4-Nitrophenol; Covalent bond; Catalysis; Colloidal gold; Chemistry; Nitrophenol; Nanoparticle; Combinatorial chemistry; Selective catalytic reduction; Photochemistry; Nanotechnology; Organic chemistry; Materials science","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007422953,0.0003503391,0.0004950529,0.0001273292,0.0002663376,0.0003216047,0.0006144905,0.0002629513,0.001784477],"category_scores_gemma":[0.0001365944,0.0002657395,0.0001026394,0.0006579814,0.0002539222,0.0001526075,0.0001946691,0.0001458603,0.0005438649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001735992,"about_ca_system_score_gemma":0.0001287305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005070465,"about_ca_topic_score_gemma":0.000004098412,"domain_scores_codex":[0.9972994,0.0000716222,0.0009389299,0.0007270497,0.000463087,0.0004999473],"domain_scores_gemma":[0.9977546,0.0007585436,0.0002972718,0.0009657087,0.00014034,0.00008357978],"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":[0.0002026611,0.00008366701,0.000001388324,0.0002615605,0.00009346957,8.467054e-7,0.0002868604,0.00005395273,0.9713603,0.02488429,0.002116403,0.0006546232],"study_design_scores_gemma":[0.0003816902,0.00005757973,0.00003614114,0.0001244192,0.0003099423,0.00002911494,0.0001337214,0.00001605898,0.9783877,0.01424524,0.005997619,0.0002807998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880006,0.001361232,0.004433301,0.0008154863,0.002507198,0.002021166,0.0003779268,0.0004318988,0.00005121942],"genre_scores_gemma":[0.9959044,0.0002049704,0.001482046,0.0001146278,0.000518859,0.001313716,0.00009369457,0.0001104347,0.0002572139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01063905,"threshold_uncertainty_score":0.9999795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924118385569977,"score_gpt":0.2603154803059257,"score_spread":0.241074296450226,"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."}}