{"id":"W3008746174","doi":"10.18331/brj2020.7.1.5","title":"Biorefinery perspectives of microbial electrolysis cells (MECs) for hydrogen and valuable chemicals production through wastewater treatment","year":2020,"lang":"en","type":"article","venue":"Biofuel Research Journal","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Kebangsaan Malaysia","keywords":"Microbial electrolysis cell; Microbial fuel cell; Renewable energy; Biorefinery; Biochemical engineering; Environmental science; Energy recovery; Hydrogen production; Process engineering; Anaerobic digestion; Environmentally friendly; Waste management; Biofuel; Electricity generation; Chemistry; Engineering; Hydrogen; Energy (signal processing); Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006386667,0.0001253512,0.000190702,0.00004974224,0.0002274508,0.00005938206,0.0001503374,0.00007650156,0.0005406815],"category_scores_gemma":[0.0001109036,0.00008885384,0.0001067614,0.0002792758,0.0002548384,0.0002016707,0.00008947436,0.0001698103,0.00003213586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002451374,"about_ca_system_score_gemma":0.00004959725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000089819,"about_ca_topic_score_gemma":0.000009789115,"domain_scores_codex":[0.9985099,0.0001189983,0.0002547405,0.0003477657,0.0003645108,0.0004040302],"domain_scores_gemma":[0.9995224,0.0000447501,0.0001003893,0.0001063986,0.00006715979,0.0001588891],"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":[0.0002401328,0.0001380345,0.0004963428,0.00003267084,0.00003764603,0.000001683232,0.001986752,0.00002559462,0.9915929,0.000003127328,0.004063807,0.001381318],"study_design_scores_gemma":[0.000547185,0.000719067,0.00006557393,0.00000896763,0.00002513347,0.00001622268,0.0005200397,0.0001137006,0.9844403,0.0003278201,0.01311863,0.00009738768],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953832,0.0006405194,0.00003964411,0.003253271,0.000048527,0.0004232606,0.00002237682,0.00000774182,0.0001814553],"genre_scores_gemma":[0.9937749,0.002603965,0.002611351,0.00003638104,0.0005311192,0.00001396733,0.000008326066,0.00001593194,0.0004040767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009054824,"threshold_uncertainty_score":0.5920084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0547854787132857,"score_gpt":0.3051130982514758,"score_spread":0.2503276195381901,"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."}}