{"id":"W4388848410","doi":"10.1016/j.bej.2023.109155","title":"Bibliometric analysis of research trends in microbial fuel cells for wastewater treatment","year":2023,"lang":"en","type":"article","venue":"Biochemical Engineering Journal","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Microbial fuel cell; Sewage treatment; Wastewater; Environmental science; Waste management; Pulp and paper industry; Biochemical engineering; Chemistry; Environmental engineering; 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":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00347252,0.0005702092,0.001398825,0.06745585,0.0009277923,0.003506168,0.000686934,0.0005816622,0.003068535],"category_scores_gemma":[0.02789622,0.0001726106,0.001781661,0.1096527,0.0004398842,0.001595099,0.00106501,0.0005600858,0.0009527693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001687575,"about_ca_system_score_gemma":0.003434436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007997465,"about_ca_topic_score_gemma":0.01280315,"domain_scores_codex":[0.991939,0.001064506,0.00180188,0.0009812346,0.003755827,0.000457521],"domain_scores_gemma":[0.9667873,0.0171145,0.006026396,0.0008317607,0.008382699,0.0008573423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00090609,0.0003131818,0.6630487,0.01381971,0.004616618,0.0005499606,0.001047963,0.005275806,0.0185547,0.00309562,0.01632751,0.2724441],"study_design_scores_gemma":[0.00005563201,0.0003425234,0.9085711,0.000917772,0.002600318,0.001287607,0.001692472,0.01080483,0.009043753,0.002669771,0.06188099,0.0001332054],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7323917,0.05774135,0.005312477,0.001724052,0.0004195471,0.0002548275,0.1774498,0.0009694052,0.02373691],"genre_scores_gemma":[0.8952139,0.01754074,0.008551747,0.0001917041,0.0003491229,0.0002631596,0.07497356,0.0001076465,0.002808508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9325442,"threshold_uncertainty_score":0.01836467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03134486947288326,"score_gpt":0.2917924260973652,"score_spread":0.2604475566244819,"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."}}