{"id":"W2581394907","doi":"10.1016/j.jpowsour.2017.01.062","title":"Carbon source and energy harvesting optimization in solid anolyte microbial fuel cells","year":2017,"lang":"en","type":"article","venue":"Journal of Power Sources","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"Ministerio de Economía y Competitividad","keywords":"Sawdust; Humus; Renewable energy; Microbial fuel cell; Environmental science; Peat; Waste management; Electricity generation; Pulp and paper industry; Environmental engineering; Power (physics); Engineering; Electrical engineering; Soil water; Ecology; Soil science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001636865,0.0003197823,0.0003483657,0.0003585767,0.000231427,0.0008417392,0.0002832135,0.0003639341,0.001063133],"category_scores_gemma":[0.0003459388,0.0001255508,0.0001750973,0.0004410443,0.0001295215,0.0004285188,0.0002534945,0.0002687458,0.0001455612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000383542,"about_ca_system_score_gemma":0.0002917303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001240002,"about_ca_topic_score_gemma":0.002862504,"domain_scores_codex":[0.9999274,0.00001011546,0.000005560051,0.00001346758,0.00002953547,0.0000138612],"domain_scores_gemma":[0.999929,0.00003715698,0.000007667154,0.000003413625,0.0000174731,0.000005285377],"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":[0.000701798,0.0005736034,0.002070871,0.0003322367,0.0000603163,0.0001233034,0.00003972988,0.1333034,0.813686,0.00204102,0.0003699106,0.04669777],"study_design_scores_gemma":[0.00004832393,0.0005297096,0.002298921,0.00001916391,0.0000425548,0.00004862989,0.000109558,0.3283794,0.6658555,0.001125823,0.001513837,0.00002870025],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907389,0.0009880301,0.005421978,0.0001104115,0.00001519104,0.0000151622,0.000114013,0.0000259655,0.002570323],"genre_scores_gemma":[0.9957725,0.0005549403,0.002737398,0.00001484987,0.000003659022,0.00001287023,0.00009219951,0.00001581804,0.0007956725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001240002,"threshold_uncertainty_score":0.00355655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00557050523544779,"score_gpt":0.1979205039122454,"score_spread":0.1923499986767976,"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."}}