{"id":"W3197055594","doi":"10.18331/brj2021.8.3.2","title":"Distillery decarbonisation and anaerobic digestion: balancing benefits and drawbacks using a compromise programming approach","year":2021,"lang":"en","type":"article","venue":"Biofuel Research Journal","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science Foundation Ireland; Pernod Ricard; European Commission","keywords":"Stillage; Anaerobic digestion; Scope (computer science); Electricity; Greenhouse gas; Waste management; Environmental science; Engineering; Computer science; Fermentation; Chemistry; Food science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003871229,0.002104185,0.001191227,0.001399326,0.0006692644,0.003392076,0.001504697,0.001463476,0.00270114],"category_scores_gemma":[0.005106689,0.001119197,0.001619465,0.001143466,0.0006555723,0.001837007,0.002033802,0.001524538,0.0002640588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001516131,"about_ca_system_score_gemma":0.001631421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002996817,"about_ca_topic_score_gemma":0.002814114,"domain_scores_codex":[0.998384,0.0008216747,0.00005945724,0.0002418907,0.0002698689,0.0002231177],"domain_scores_gemma":[0.9970284,0.002232807,0.0002993235,0.00007491105,0.0002655792,0.0000990846],"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":[0.0001730155,0.0001082459,0.001391861,0.0001822901,0.0001180751,0.0001342445,0.0001160853,0.9597902,0.003007205,0.005662519,0.0002207703,0.0290955],"study_design_scores_gemma":[0.00002931867,0.0003515386,0.0004181491,0.00005901452,0.0000871665,0.00005092666,0.0001181828,0.9883801,0.002265504,0.006899991,0.001313995,0.00002605521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.246814,0.001109576,0.7248781,0.0005739752,0.00007205227,0.0005900259,0.0001723452,0.0003168308,0.0254732],"genre_scores_gemma":[0.7779363,0.0005361108,0.2150043,0.0001656033,0.00002510738,0.0006489992,0.0001523035,0.0001089029,0.005422472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003871229,"threshold_uncertainty_score":0.0204733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06258325210042805,"score_gpt":0.3138064190312405,"score_spread":0.2512231669308124,"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."}}