{"id":"W4404956370","doi":"10.1016/j.biortech.2024.131936","title":"Trace concentrations of graphene oxide and magnetic graphene oxide rescue anaerobic municipal sludge digesters under stress","year":2024,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Island University; Okanagan University College; University of British Columbia, Okanagan Campus","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Graphene; Oxide; Anaerobic digestion; Chemical oxygen demand; Anaerobic exercise; Chemistry; Pulp and paper industry; Waste management; Materials science; Environmental science; Methane; Environmental engineering; Wastewater; Nanotechnology; Metallurgy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001025234,0.0002352556,0.0001708277,0.0001791535,0.0001166671,0.0002527182,0.0001560893,0.0003814044,0.0006613463],"category_scores_gemma":[0.0001680195,0.00009824656,0.0001989366,0.0001102557,0.0001411954,0.0001906053,0.0001857873,0.0002302677,0.0001104013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001911553,"about_ca_system_score_gemma":0.00009591693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008036898,"about_ca_topic_score_gemma":0.002063416,"domain_scores_codex":[0.9998977,0.000009606923,0.000007425914,0.00002750361,0.00003471779,0.00002306756],"domain_scores_gemma":[0.9999287,0.0000106682,0.00001826128,0.000007126671,0.00002188647,0.00001336106],"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":[0.00005228415,0.000006131351,0.0001686435,0.00001612313,0.000002302504,0.00001514465,0.000008331205,0.00007817145,0.9989505,0.000008720675,0.00001308987,0.0006806408],"study_design_scores_gemma":[0.000003541362,0.0002175836,0.002717701,0.000003951184,0.000009226436,0.0000203319,0.00003597527,0.0008673141,0.9955245,0.00002197237,0.0005735235,0.000004300819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998521,0.0001565566,0.0007855323,0.00002849896,0.00001395727,0.000007888016,0.0001149744,0.00003392177,0.0003376816],"genre_scores_gemma":[0.9972064,0.0001144658,0.001186024,0.00002552973,0.00000400729,0.00001364733,0.000183514,0.000011643,0.001254713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008036898,"threshold_uncertainty_score":0.002212405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205575079654917,"score_gpt":0.2373653730165191,"score_spread":0.22530962221997,"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."}}