{"id":"W2883352600","doi":"10.1002/sd.1848","title":"Using multi‐criteria decision analysis for assessing sustainability of agricultural systems","year":2018,"lang":"en","type":"article","venue":"Sustainable Development","topic":"Sustainable Agricultural Systems Analysis","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Centre for International Governance Innovation; Balsillie School of International Affairs; McGill University Health Centre; University of Waterloo; McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Sustainability; Multiple-criteria decision analysis; Weighting; Environmental Sustainability Index; Agriculture; Environmental economics; Composite indicator; Business; Sustainability organizations; Environmental resource management; Environmental science; Operations research; Engineering; Economics; Geography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001770894,0.0003879802,0.0007685696,0.0003364964,0.0008601545,0.0002733819,0.0004817115,0.0001725433,0.0002881884],"category_scores_gemma":[0.000625333,0.0002794831,0.0003136796,0.003840551,0.0002523396,0.0008673058,0.0005393716,0.00009157172,0.00001358114],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004621076,"about_ca_system_score_gemma":0.0002416619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004601417,"about_ca_topic_score_gemma":0.0002684334,"domain_scores_codex":[0.9961239,0.0001770084,0.001089014,0.0008148544,0.0007034618,0.001091769],"domain_scores_gemma":[0.9971876,0.000166208,0.0005363738,0.0004794958,0.00141537,0.0002149717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001786923,0.0006946276,0.8539027,0.001441089,0.002186097,0.00006080706,0.007911135,0.1184087,0.008318882,0.0009865203,0.001524842,0.004385923],"study_design_scores_gemma":[0.0007174771,0.00007018753,0.8749005,0.00004769055,0.000622257,0.00001019857,0.09576255,0.01752982,0.002665384,0.0001774001,0.006795403,0.0007011302],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8184686,0.00007537881,0.1796425,0.00002793263,0.0001273238,0.001262725,0.000003507676,0.00005179083,0.0003402229],"genre_scores_gemma":[0.9587257,0.000001113616,0.03754805,0.00001006993,0.00007955249,0.0001560714,0.00003573674,0.00002076716,0.003422962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1420944,"threshold_uncertainty_score":0.9999657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0223051219615736,"score_gpt":0.3006776656284211,"score_spread":0.2783725436668475,"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."}}