{"id":"W4409434058","doi":"10.3390/app15084248","title":"Non-Thermal Plasma-Catalytic Conversion of Biogas to Value-Added Liquid Chemicals via Ni-Fe/Al2O3 Catalyst","year":2025,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Catalysis; Biogas; Chemical engineering; Materials science; Waste management; Value (mathematics); Pulp and paper industry; Chemistry; Organic chemistry; Engineering; Mathematics","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":[0.0006236011,0.000260648,0.0004572287,0.000375939,0.0001497382,0.0000220939,0.0009010413,0.0001463262,0.00006336055],"category_scores_gemma":[0.0001110715,0.0002246581,0.0001267424,0.001637321,0.0003639591,0.0001583137,0.0004203017,0.0001892806,0.0001725164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001459921,"about_ca_system_score_gemma":0.0001167758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002742057,"about_ca_topic_score_gemma":0.000003946961,"domain_scores_codex":[0.997835,0.000007021717,0.0005048939,0.0005829713,0.0005293025,0.0005408307],"domain_scores_gemma":[0.9990087,0.0001715802,0.0001364199,0.0004547474,0.00005333948,0.0001752341],"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":[0.00007029727,0.00003656591,0.00003863619,0.00009971168,0.00003714998,0.000001615757,0.0002831069,0.0006449619,0.9967403,0.001363454,0.0001017288,0.00058246],"study_design_scores_gemma":[0.0004181559,0.00004920505,0.00002674836,0.00008779248,0.00005140161,0.000003598,0.000307303,0.004908439,0.9933567,0.00004809136,0.0004961016,0.0002464501],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782806,0.00005275312,0.0009062176,0.0001583844,0.0002430268,0.0003386152,0.00001067575,0.0001093198,0.01990042],"genre_scores_gemma":[0.9984698,0.000002617726,0.0009037808,0.0001183112,0.00005596014,0.00003692754,0.000023406,0.000017932,0.0003712924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02018918,"threshold_uncertainty_score":0.9161292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009323845618064078,"score_gpt":0.2451049019134996,"score_spread":0.2357810562954355,"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."}}