{"id":"W4285792131","doi":"10.1016/j.jenvman.2022.115717","title":"Post-hydrolysis ammonia stripping as a new approach to enhance the two-stage anaerobic digestion of poultry manure: Optimization and statistical modelling","year":2022,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Anaerobic Digestion and Biogas Production","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"CH Four Biogas (Canada); University of Ottawa","funders":"Ontario Centre of Innovation","keywords":"Ammonia; Chemistry; Anaerobic digestion; Digestate; Hydrolysis; Air stripping; Manure; Stripping (fiber); Methane; Ammonia volatilization from urea; Nitrogen; Environmental chemistry; Pulp and paper industry; Waste management; Environmental engineering; Environmental science; Agronomy; Organic chemistry; Materials science; Wastewater","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002832545,0.0001100048,0.0001347803,0.0001307864,0.0001088328,0.00002578246,0.0001268965,0.00001696658,0.0001352663],"category_scores_gemma":[0.000005668835,0.00009573642,0.00004214892,0.000124598,0.00002706883,0.0001358989,0.00009376195,0.0001674993,0.000003118181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001863897,"about_ca_system_score_gemma":0.000006188736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000182978,"about_ca_topic_score_gemma":3.193956e-7,"domain_scores_codex":[0.9990257,0.00004518959,0.0003282788,0.0001413353,0.0003374653,0.000122025],"domain_scores_gemma":[0.9996321,0.00001402115,0.0001335687,0.0001232516,0.000005904772,0.00009114949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004998673,0.00008766453,0.00005679735,0.00001413659,0.00008075387,0.000004806999,0.0002034056,0.9898798,0.002230024,0.001626092,0.0001925468,0.005573983],"study_design_scores_gemma":[0.002488677,0.001281849,0.006703157,0.000120193,0.0008196745,0.0002331231,0.01669585,0.9438268,0.003781194,0.0005901725,0.02255675,0.0009025542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3179411,0.0002648742,0.6804109,0.0003991176,0.0001570422,0.0002838028,0.00001868365,0.00001573283,0.0005087459],"genre_scores_gemma":[0.9532273,0.0003999668,0.04539957,0.000100009,0.0000478786,0.000007251294,0.00001860615,0.00001573708,0.0007836131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6352863,"threshold_uncertainty_score":0.3904018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006322263949076906,"score_gpt":0.2042735828124668,"score_spread":0.1979513188633899,"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."}}