{"id":"W3093608051","doi":"10.1088/2632-959x/abc2e3","title":"Boron nitride-palladium nanostructured catalyst: efficient reduction of nitrobenzene derivatives in water","year":2020,"lang":"en","type":"article","venue":"Nano Express","topic":"Nanomaterials for catalytic reactions","field":"Chemistry","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"National Research Foundation of Korea","keywords":"Nitrobenzene; Catalysis; Boron nitride; Palladium; X-ray photoelectron spectroscopy; Materials science; Scanning electron microscope; Transmission electron microscopy; Chemical engineering; Boron; Nuclear chemistry; Inorganic chemistry; Chemistry; Nanotechnology; Organic chemistry; Composite material","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00008571802,0.0002382783,0.0003959145,0.00009986129,0.00005860964,0.00003050093,0.0003021846,0.0001772715,0.00051584],"category_scores_gemma":[0.00009408373,0.0001987597,0.0001086821,0.000195113,0.00008750751,0.0001267836,0.0001261578,0.0001397421,0.00003314972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001043199,"about_ca_system_score_gemma":0.00004944812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002784126,"about_ca_topic_score_gemma":0.000005244719,"domain_scores_codex":[0.9983224,0.00003033967,0.0005793843,0.0004300136,0.0002893634,0.0003485465],"domain_scores_gemma":[0.9991802,0.00002605641,0.0001774811,0.0004119944,0.00008687311,0.0001173969],"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":[0.0001619671,0.00007471497,0.0002504063,0.000194577,0.00003480259,0.000007513476,0.003374961,0.0006135546,0.9950353,0.0000145072,0.0001237602,0.0001139345],"study_design_scores_gemma":[0.000877257,0.00002344076,0.000175303,0.00006457326,0.00003016833,0.00001799609,0.0005738335,0.00009417922,0.9968714,0.00004970172,0.001005623,0.0002165965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983428,0.00009474211,0.00004479795,0.0001992114,0.000330062,0.0001584942,0.00007426828,0.00009066596,0.000664917],"genre_scores_gemma":[0.9990661,0.00001023667,0.0002842513,0.00001628014,0.0001959097,0.00003599006,0.0002153751,0.00004198091,0.0001339297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002801127,"threshold_uncertainty_score":0.8105187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01203037953059073,"score_gpt":0.2239586040520282,"score_spread":0.2119282245214374,"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."}}