{"id":"W4404322726","doi":"10.1016/j.biortech.2024.131812","title":"Amorphous Cu/Fe nanoparticles with tandem intracellular and extracellular electron capacity for enhancing denitrification performance and recovery of co-contaminant suppressed denitrification","year":2024,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Denitrification; Extracellular; Chemistry; Amorphous solid; Nanoparticle; Environmental chemistry; Tandem; Intracellular; Chemical engineering; Extracellular polymeric substance; Electron transport chain; Materials science; Bacteria; Nanotechnology; Biochemistry; Nitrogen; Biology; Composite material; Organic chemistry; Biofilm; Engineering","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":[0.0001922362,0.0001613729,0.0001848784,0.0001395287,0.0001212552,0.00003213964,0.0001077142,0.0001585774,0.00001259873],"category_scores_gemma":[0.00001724686,0.0001289353,0.00002521337,0.0002546092,0.000389823,0.0001364225,0.00003190908,0.0001067273,0.00000886631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007950425,"about_ca_system_score_gemma":0.00001202854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000571467,"about_ca_topic_score_gemma":0.00007061118,"domain_scores_codex":[0.998968,0.00002641405,0.0002292589,0.0003823945,0.0001221701,0.0002717591],"domain_scores_gemma":[0.9995937,0.00005753642,0.00009085026,0.0001999758,0.00001281593,0.00004507549],"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":[0.0001004409,0.00004211685,0.02240409,0.0000570113,0.00002760507,0.00000525925,0.0001791337,0.000008073712,0.9670078,0.0001107847,0.00001779727,0.01003985],"study_design_scores_gemma":[0.0004051359,0.0005481498,0.004082246,0.00004330241,0.0000889365,0.0001028605,0.0001685427,0.002160197,0.9903635,0.0001802739,0.001704639,0.0001521486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951748,0.001902816,0.002139234,0.0001418949,0.00001637175,0.0004868739,0.000008357501,0.0001182633,0.00001141021],"genre_scores_gemma":[0.9928138,0.0001440234,0.006793688,0.000003287692,0.00001283096,0.00007443075,0.00001447893,0.00002094584,0.0001225301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02335573,"threshold_uncertainty_score":0.5257828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008153364433354824,"score_gpt":0.1986884420037372,"score_spread":0.1905350775703824,"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."}}