{"id":"W2886477167","doi":"10.1002/celc.201800968","title":"Flow‐Based Deacidification of <i>Geobacter sulfurreducens</i> Biofilms Depends on Nutrient Conditions: a Microfluidic Bioelectrochemical Study","year":2018,"lang":"en","type":"article","venue":"ChemElectroChem","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut universitaire de cardiologie et de pneumologie de Québec; Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Geobacter sulfurreducens; Biofilm; Geobacter; Microfluidics; Nutrient; Chemistry; Flow conditions; Environmental chemistry; Flow (mathematics); Biochemical engineering; Bacteria; Nanotechnology; Biology; Materials science; Mechanics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001994184,0.0002193858,0.0001829363,0.0001198205,0.0001481355,0.0003301619,0.0002361038,0.0002694247,0.0003006312],"category_scores_gemma":[0.000146039,0.0001050336,0.000220968,0.00009399179,0.0002295638,0.0002471478,0.0001833965,0.0002730021,0.00006598012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002944856,"about_ca_system_score_gemma":0.0002092509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001431298,"about_ca_topic_score_gemma":0.00115132,"domain_scores_codex":[0.9999279,0.000009455786,0.000005160573,0.0000180572,0.00002013715,0.00001938812],"domain_scores_gemma":[0.9999468,0.00001449,0.0000130655,0.000004516206,0.00001161144,0.000009537805],"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":[0.00003188866,0.00002038888,0.0001895996,0.00001505315,0.000002696201,0.00001326661,0.00001685004,0.00008495527,0.998859,0.00003722385,0.00001554345,0.000713466],"study_design_scores_gemma":[0.0000160308,0.0002474087,0.00371521,0.000003085759,0.000009550682,0.00004395497,0.00004943395,0.002657792,0.9926951,0.00004580172,0.0005086253,0.000008028037],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983175,0.0002381842,0.001024755,0.00005715696,0.00001071158,0.00001500805,0.00005937508,0.00001711952,0.0002601589],"genre_scores_gemma":[0.9981933,0.0001907133,0.001258128,0.00002404957,0.000006522601,0.00001194869,0.00005873656,0.000003378164,0.0002531241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001431298,"threshold_uncertainty_score":0.002845883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009061601786199212,"score_gpt":0.2375091066273362,"score_spread":0.2284475048411369,"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."}}