{"id":"W4406834295","doi":"10.1016/j.apsusc.2025.162545","title":"Ab initio study of atomically dispersed catalysts on original and B-doped corrugated carbon nitride surface for effective nitrogen reduction","year":2025,"lang":"en","type":"article","venue":"Applied Surface Science","topic":"Ammonia Synthesis and Nitrogen Reduction","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Ab initio; Nitride; Materials science; Catalysis; Doping; Carbon fibers; Nitrogen; Carbon nitride; Reduction (mathematics); Chemical engineering; Nanotechnology; Chemistry; Optoelectronics; Composite material; Composite number; Organic chemistry; Photocatalysis; Layer (electronics); Geometry; Engineering","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":[0.0006309457,0.0002381997,0.0003791323,0.0001368112,0.0002297081,0.00003929378,0.000254299,0.0000851573,0.000002915111],"category_scores_gemma":[0.0001322254,0.0002225019,0.00005128125,0.0009842736,0.0003300527,0.0001054848,0.00007440095,0.0001841809,0.000003563097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002228251,"about_ca_system_score_gemma":0.0001333731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003380601,"about_ca_topic_score_gemma":0.00001017372,"domain_scores_codex":[0.9982204,0.00003475687,0.0003465056,0.0006639319,0.0003715447,0.0003628245],"domain_scores_gemma":[0.9989797,0.0002666273,0.0001377356,0.0003322728,0.0001777881,0.0001058467],"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":[0.0005342391,0.0002628344,0.0009979614,0.00004443911,0.00006480076,5.941026e-7,0.0004340409,0.005959317,0.9894024,0.001486089,0.00001921391,0.0007940693],"study_design_scores_gemma":[0.001242479,0.0001627269,0.000629351,0.00004117134,0.00009817701,0.000002616586,0.001683092,0.01333177,0.9823458,0.0002209712,0.000026865,0.0002150081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968816,0.00005563586,0.0003167766,0.00004542719,0.0001913219,0.001519654,0.00001232725,0.00009179919,0.0008854477],"genre_scores_gemma":[0.998844,0.000006399328,0.000958142,0.000009607679,0.00002453781,0.0000781494,0.000006427565,0.00002064638,0.00005210528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007372454,"threshold_uncertainty_score":0.9073363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008873251314895558,"score_gpt":0.2528714254568207,"score_spread":0.2439981741419251,"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."}}