{"id":"W4360980564","doi":"10.1007/s10113-023-02043-0","title":"Climate change–driven agricultural frontiers and their ecosystem trade-offs in the hills of Nepal","year":2023,"lang":"en","type":"article","venue":"Regional Environmental Change","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Climate change; Agriculture; Food security; Agroforestry; Geography; Environmental science; Land use; Greenhouse gas; Agricultural land; Land cover; Climate change mitigation; Environmental protection; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000298071,0.00008723989,0.0001856607,0.0006427216,0.0006763593,0.001772667,0.0003933003,0.0003672655,0.003752382],"category_scores_gemma":[0.0009536472,0.0001377455,0.0001832049,0.0009293672,0.001026691,0.001155774,0.00113746,0.0003111843,0.0001759035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001928261,"about_ca_system_score_gemma":0.0005804974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03413089,"about_ca_topic_score_gemma":0.1199476,"domain_scores_codex":[0.9998392,0.00004567427,0.000005990126,0.00001984254,0.00001209422,0.00007730594],"domain_scores_gemma":[0.9995492,0.0001757998,0.00009112131,0.00001900152,0.00006382793,0.0001009444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001094961,0.0002107569,0.880972,0.0002860734,0.0002945781,0.003588857,0.01374024,0.01297863,0.01075995,0.04162379,0.001527091,0.03292317],"study_design_scores_gemma":[0.00001329094,0.00003458626,0.9795083,0.00002530517,0.00002145988,0.0002171381,0.01000836,0.003642078,0.0001539261,0.004405393,0.001956161,0.00001390587],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950764,0.0001573272,0.00005224445,0.000173838,0.000001361869,0.000002727964,0.00008162355,0.000001937882,0.004452661],"genre_scores_gemma":[0.9995962,0.00003904903,0.0000259196,0.000008787402,0.000001123523,0.000001451274,0.00001809424,9.616302e-7,0.0003085327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03413089,"threshold_uncertainty_score":0.06786448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05993912559831746,"score_gpt":0.2154422172075948,"score_spread":0.1555030916092773,"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."}}