{"id":"W2224652958","doi":"10.1016/j.wasman.2015.12.032","title":"Optimizing the performance of microbial fuel cells fed a combination of different synthetic organic fractions in municipal solid waste","year":2016,"lang":"en","type":"article","venue":"Waste Management","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Windsor; U.S. Environmental Protection Agency","keywords":"Microbial fuel cell; Chemical oxygen demand; Pulp and paper industry; Municipal solid waste; Waste management; Raw material; Microbial consortium; Biodegradable waste; Environmental science; Biofuel; Biomass (ecology); Food waste; Bioenergy; Electricity generation; Chemistry; Wastewater; Environmental engineering; Microorganism; Biology; Agronomy; Anode; Engineering; Organic chemistry","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":[0.000227089,0.0001115821,0.0001415555,0.00006532287,0.0000548608,0.000009991984,0.0002533475,0.00003481575,0.0005406947],"category_scores_gemma":[0.000004359115,0.00006684352,0.00004879141,0.0001881195,0.0001072503,0.00009850194,0.0002731905,0.00005655086,0.00005000243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001359709,"about_ca_system_score_gemma":0.000002582756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005874767,"about_ca_topic_score_gemma":0.0001902916,"domain_scores_codex":[0.9990347,0.00005948793,0.0003258858,0.0001846875,0.0002077481,0.0001874937],"domain_scores_gemma":[0.999471,0.00003596411,0.0001921831,0.0002681416,0.000008597826,0.0000241161],"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":[0.00004198285,0.0002420229,0.0007971652,0.0001018992,0.00001611825,6.774154e-7,0.0006922221,0.001460395,0.9939556,0.00005595801,0.0001239961,0.002511932],"study_design_scores_gemma":[0.001499872,0.0002592722,0.007465938,0.0002732159,0.00006988437,0.000001023189,0.001205087,0.007938686,0.9803507,0.0000697486,0.0006412815,0.0002252588],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975181,0.0000131033,0.0001897548,0.0002112482,0.0001808262,0.0003840191,0.000004727375,0.000006786152,0.001491415],"genre_scores_gemma":[0.9987005,0.0003487839,0.0001928837,0.00002590914,0.00001484707,0.00001099312,0.000002921046,0.000009581304,0.0006935931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0136049,"threshold_uncertainty_score":0.5920228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006623933143846018,"score_gpt":0.1920956687224068,"score_spread":0.1854717355785608,"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."}}