{"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":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.0006119314,0.00009179,0.0001849325,0.03077142,0.00002776692,0.00002869376,0.0001484373,0.00008272519,0.0004035363],"category_scores_gemma":[0.00004418577,0.00007281635,0.0001681767,0.09309164,0.00003579609,0.00004698917,0.00005636031,0.0001154059,0.00002681398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002492408,"about_ca_system_score_gemma":0.000006800738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005120416,"about_ca_topic_score_gemma":0.000007701618,"domain_scores_codex":[0.9989413,0.00001717431,0.000275746,0.000170389,0.0002499759,0.0003454006],"domain_scores_gemma":[0.999648,0.00009159608,0.00004366857,0.00009957264,0.00001833529,0.0000988223],"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":[0.00001987709,0.00006008978,0.001464424,0.00001351993,0.00005116792,0.000003875648,0.00008392699,0.01558044,0.9774461,7.020137e-7,0.003329777,0.001946103],"study_design_scores_gemma":[0.0007226556,0.0001705654,0.04570279,0.00001674992,0.00009037312,0.000003794422,0.00001842009,0.03150637,0.9154747,0.000007898165,0.006127286,0.0001584668],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994966,0.00006602288,0.00008012753,0.00007976456,0.0001266459,0.00006635808,0.00002631551,0.00001339482,0.00004471752],"genre_scores_gemma":[0.9981948,0.0002084123,0.001139741,0.000002959799,0.00009986258,0.00000607796,0.00004333247,0.00001038546,0.0002944599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06232022,"threshold_uncertainty_score":0.9802139,"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."}}