{"id":"W2969499597","doi":"10.1002/cjce.23568","title":"Removal of heavy metals in a flow‐through vertical microbial electrolysis cell","year":2019,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of National Defence; National Research Council Canada","funders":"","keywords":"Effluent; Chemistry; Environmental chemistry; Electrolysis; Metal; Peat; Carbon fibers; Pulp and paper industry; Environmental engineering; Environmental science; Electrode; Materials science; Electrolyte; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.000246095,0.00008226021,0.000183305,0.00004159374,0.00001219481,0.00001261605,0.000223736,0.00006472212,0.0005173872],"category_scores_gemma":[0.00004640653,0.00006185793,0.00009240382,0.0002109329,0.00004539212,0.00008471713,0.00001821683,0.0002336053,0.00002846921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002462287,"about_ca_system_score_gemma":0.00007328911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002065563,"about_ca_topic_score_gemma":0.0005883976,"domain_scores_codex":[0.999234,0.00001472507,0.0002919503,0.00007830762,0.0001403943,0.0002405913],"domain_scores_gemma":[0.9996732,0.00003683698,0.00005172631,0.00009645525,0.0000111753,0.0001306074],"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":[0.00001590902,0.000008246052,0.0002671117,0.00001140171,0.000007139548,0.00002047263,0.0001701145,0.0165446,0.9827075,0.00001249283,0.0001492376,0.00008578414],"study_design_scores_gemma":[0.0003355403,0.00003467579,0.0002275232,0.00002494874,0.00002079766,0.0001282623,0.000004886607,0.006447525,0.9903973,0.0000404183,0.002242686,0.00009539093],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998858,0.0001567721,0.0001042702,0.0002474294,0.0001146965,0.00005956722,0.000002137592,0.000001671425,0.00045542],"genre_scores_gemma":[0.9982842,0.000004283937,0.001546698,0.00007169441,0.00005746256,2.76616e-7,0.000001109341,0.000008603552,0.00002570025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01009707,"threshold_uncertainty_score":0.5665027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003606064171479821,"score_gpt":0.1585758482586197,"score_spread":0.1549697840871399,"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."}}