{"id":"W3023180416","doi":"10.1016/j.indic.2020.100038","title":"Towards complexity of agricultural sustainability assessment: Main issues and concerns","year":2020,"lang":"en","type":"article","venue":"Environmental and Sustainability Indicators","topic":"Sustainable Agricultural Systems Analysis","field":"Environmental Science","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Queen's University; Wilfrid Laurier University; Centre for International Governance Innovation; Balsillie School of International Affairs; York University","funders":"","keywords":"Sustainability; Resilience (materials science); Corporate governance; Agriculture; Sustainability science; Environmental resource management; Psychological resilience; Sustainability organizations; Adaptation (eye); Set (abstract data type); Environmental planning; Business; Management science; Process management; Risk analysis (engineering); Computer science; Engineering; Geography; Economics; Psychology; Ecology","routes":{"ca_aff":true,"ca_fund":false,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004980361,0.0003776691,0.0005924223,0.00004776846,0.0003323955,0.00005689798,0.0002962349,0.0001503887,0.001117057],"category_scores_gemma":[0.0001763673,0.0002766212,0.0001461429,0.0004530943,0.002695888,0.0004320003,0.0009472211,0.0002734633,0.000007771027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001481091,"about_ca_system_score_gemma":0.0000501424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00259593,"about_ca_topic_score_gemma":0.00004996794,"domain_scores_codex":[0.9970891,0.0003351503,0.0005921148,0.0008352887,0.0006025849,0.000545765],"domain_scores_gemma":[0.9988497,0.0000659848,0.0002644486,0.0002937001,0.00001805876,0.0005080883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002942201,0.0001739777,0.9888543,0.0002644213,0.00005886317,0.00001382118,0.003812959,0.000121922,0.0008708225,0.001391581,0.000299546,0.004108401],"study_design_scores_gemma":[0.0004097935,0.0002336273,0.9399915,0.00000348069,0.00006603028,0.000009259319,0.05312493,0.0001311681,0.0004155825,0.003140059,0.00213361,0.0003409767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902161,0.0002420443,0.00007603476,0.007836943,0.00001703233,0.000952985,0.00006246545,0.00004811206,0.0005482631],"genre_scores_gemma":[0.999199,0.00006555137,0.0002360794,0.0001423029,0.0000466349,0.00004638043,0.0000367262,0.00001346861,0.000213795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04931197,"threshold_uncertainty_score":0.9999686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00923717109126095,"score_gpt":0.2435080006700289,"score_spread":0.234270829578768,"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."}}