{"id":"W2348943026","doi":"","title":"Diverse Microbial Communities in Microbial Fuel Cells with Sugar Beet Residue as Substrate","year":2015,"lang":"en","type":"article","venue":"Anhui nongye kexue","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Microbial fuel cell; Microbial population biology; Bacteria; Pyrosequencing; Microbial consortium; Acidogenesis; Sugar beet; Food science; Cellulose; Sugar; Biofilm; Pulp and paper industry; Anode; Biology; Chemistry; Biochemistry; Microorganism; Ecology; Anaerobic digestion; Agronomy","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004319294,0.0002591608,0.0002378128,0.00008049596,0.000120501,0.00009690973,0.0004258651,0.0001553685,0.001350439],"category_scores_gemma":[0.00001050961,0.000226006,0.00005061838,0.0003266956,0.0003609603,0.000351696,0.000245674,0.0002803518,0.001792933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002204852,"about_ca_system_score_gemma":0.00007030764,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0295852,"about_ca_topic_score_gemma":0.1098208,"domain_scores_codex":[0.9984778,0.0001537283,0.0002986205,0.000317097,0.0002707244,0.0004820316],"domain_scores_gemma":[0.9992508,0.00004177288,0.0001206945,0.0003670425,0.00002925432,0.0001904745],"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":[0.0009826893,0.0006757885,0.1707271,0.00008402124,0.00003674264,0.0003189681,0.01375153,0.00258809,0.7359617,0.00008389918,0.07373232,0.001057132],"study_design_scores_gemma":[0.01355532,0.002300672,0.1047592,0.0003156305,0.00016405,0.0002265835,0.01951014,0.0003926257,0.695265,0.00101645,0.1590833,0.003411019],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985059,0.00004224898,0.00001078843,0.0001789795,0.0002889739,0.000334333,0.00005469876,0.0000405334,0.0139905],"genre_scores_gemma":[0.996637,0.00008883425,0.0007638874,0.0005254076,0.0001243347,0.000006994373,0.000131373,0.00002797206,0.001694135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08535095,"threshold_uncertainty_score":0.9995624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01734046513430182,"score_gpt":0.2074642315726268,"score_spread":0.190123766438325,"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."}}