{"id":"W2808018527","doi":"10.3390/su10061990","title":"Institutional Perspectives of Climate-Smart Agriculture: A Systematic Literature Review","year":2018,"lang":"en","type":"article","venue":"Sustainability","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Centre for International Agricultural Research; International Fund for Agricultural Development; Government of the United Kingdom; Consortium of International Agricultural Research Centers; European Commission; International Development Research Centre; Department for International Development","keywords":"Agriculture; Climate change; Systematic review; Environmental planning; Environmental resource management; Natural resource economics; Regional science; Business; Political science; Geography; Environmental science; Economics; MEDLINE; Ecology; Archaeology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007513423,0.000242717,0.0005213125,0.0000160669,0.0002715266,0.0000605107,0.0003252785,0.0001539876,0.0003835727],"category_scores_gemma":[0.002282615,0.00007263943,0.0002339072,0.001238162,0.0003257807,0.0002708769,0.0001383644,0.0001777205,0.00002091495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003771865,"about_ca_system_score_gemma":0.00004070155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004813964,"about_ca_topic_score_gemma":0.0003098386,"domain_scores_codex":[0.9980674,0.0002550099,0.0004701656,0.0004212272,0.0003708963,0.0004153185],"domain_scores_gemma":[0.99659,0.0001658704,0.000250976,0.0001632189,0.00268904,0.0001408807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"observational","study_design_scores_codex":[0.0004741636,0.004162566,0.03259291,0.7918798,0.0003583887,0.0001596804,0.02057368,0.000002850298,0.06769827,0.04167312,0.02890972,0.01151491],"study_design_scores_gemma":[0.0009918717,0.003218301,0.7415189,0.1500925,0.0006562826,0.0006670774,0.06478437,0.00002941556,0.004028743,0.005954074,0.02567866,0.002379838],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9011998,0.0819357,0.000002350014,0.01029796,0.0001992032,0.003189315,0.0003796176,0.0002006716,0.002595363],"genre_scores_gemma":[0.9878468,0.01105929,0.00003582785,0.0003541158,0.0003270351,0.00009019814,0.0001378295,0.000001071178,0.0001478318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.708926,"threshold_uncertainty_score":0.4199851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01254999333304515,"score_gpt":0.2629250543803021,"score_spread":0.2503750610472569,"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."}}