{"id":"W7045580935","doi":"","title":"Ammonia recovery from simulated food liquid digestate using bipolar membrane electrodialysis","year":2023,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Astronomy and Astrophysical Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada","keywords":"Electrodialysis; Ammonia; Digestate; Membrane; Reversed electrodialysis; Membrane technology; Wastewater; Nitrogen","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":[0.0001883135,0.0004043595,0.000263162,0.0002139549,0.000156739,0.0003002165,0.0003033425,0.0004576136,0.0003693197],"category_scores_gemma":[0.000209053,0.0001385179,0.0002272591,0.0002365958,0.0001257522,0.0003125252,0.0002736932,0.0004141797,0.0001841424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003583312,"about_ca_system_score_gemma":0.0001921388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001678282,"about_ca_topic_score_gemma":0.001913529,"domain_scores_codex":[0.9998286,0.00002640982,0.00001400435,0.00004906095,0.00005822983,0.0000237348],"domain_scores_gemma":[0.9999355,0.00001486365,0.00001578333,0.000003882157,0.00002250227,0.000007505396],"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":[0.00002622244,0.000004896537,0.00003734328,0.0000150567,0.000001417854,0.000008201853,0.000004125083,0.00003171363,0.9992114,0.000004851264,0.000007172214,0.0006475655],"study_design_scores_gemma":[0.000005099744,0.0001378491,0.0006215364,0.000002371045,0.000004937155,0.00002448052,0.00001237053,0.0006924376,0.9981659,0.000006036829,0.0003230965,0.000003930548],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915807,0.0006103304,0.006474121,0.00009913185,0.00002110701,0.00003773153,0.0002895092,0.0001044222,0.0007828588],"genre_scores_gemma":[0.9842695,0.001095839,0.01274762,0.00005543938,0.000007033782,0.00004239673,0.0003409237,0.00001992043,0.001421428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001678282,"threshold_uncertainty_score":0.003337026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0139346771908164,"score_gpt":0.2304942480523232,"score_spread":0.2165595708615068,"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."}}