{"id":"W4411586738","doi":"10.1021/acsestengg.5c00163","title":"Simultaneous Biogas Upgrading and Desulfurization Using a Microbial Electrosynthesis System with Optimized Electrodes and Membrane Selection","year":2025,"lang":"en","type":"article","venue":"ACS ES&T Engineering","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Electrosynthesis; Flue-gas desulfurization; Biogas; Electrode; Selection (genetic algorithm); Membrane; Chemical engineering; Waste management; Chemistry; Pulp and paper industry; Process engineering; Environmental science; Biochemical engineering; Materials science; Computer science; Engineering; Electrochemistry; Biochemistry; Artificial intelligence","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":[0.0002730463,0.0007230496,0.0004403459,0.000267715,0.0001264071,0.0004322881,0.0003121697,0.0004985174,0.0006521129],"category_scores_gemma":[0.0002219575,0.0002198637,0.0002501503,0.0002172553,0.0001741711,0.000575693,0.0005286583,0.0004119667,0.0003068676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001730623,"about_ca_system_score_gemma":0.0001876805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001791491,"about_ca_topic_score_gemma":0.0004506067,"domain_scores_codex":[0.9998214,0.00002566778,0.00002019175,0.00004849628,0.00005849696,0.00002580917],"domain_scores_gemma":[0.9999449,0.00001257788,0.00001271049,0.000004787126,0.00001283288,0.00001207023],"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":[0.00002345204,0.000006173043,0.00003985774,0.00001830124,0.000002537506,0.00001299839,0.000003248876,0.00006954748,0.9988181,0.00002011799,0.000009025155,0.0009766266],"study_design_scores_gemma":[0.000006431874,0.00006571977,0.0003627669,0.000002062704,0.000006894658,0.00003357096,0.00000915389,0.001037548,0.9978205,0.00001751502,0.0006327712,0.000005173314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726751,0.001189579,0.02422948,0.0001044617,0.00005116533,0.00007040825,0.0002532519,0.0002628267,0.001163671],"genre_scores_gemma":[0.9545496,0.0009698427,0.04182507,0.00006404582,0.00001982818,0.0001234846,0.0003199886,0.00004451293,0.002083621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007230496,"threshold_uncertainty_score":0.00218153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002311759611370438,"score_gpt":0.1631870934201707,"score_spread":0.1608753338088002,"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."}}