{"id":"W3009453178","doi":"10.1016/j.jenvman.2020.110326","title":"Spatio-temporal evolution of agricultural land use change drivers: A case study from Chalous region, Iran","year":2020,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Land use; Agriculture; Land cover; Geography; Elevation (ballistics); Environmental resource management; Agricultural land; Land use, land-use change and forestry; Land management; Geographic information system; Population; Driving factors; Physical geography; Cartography; Environmental science; Engineering; Civil engineering","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":[0.0003010922,0.0001711776,0.000178848,0.001024499,0.0007067784,0.0005501518,0.0005095714,0.0003669233,0.0008676945],"category_scores_gemma":[0.0005931482,0.0001263767,0.0003458404,0.001756659,0.0003887982,0.0003492942,0.0004667646,0.0003019327,0.0000985626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420921,"about_ca_system_score_gemma":0.001155091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1108503,"about_ca_topic_score_gemma":0.1929668,"domain_scores_codex":[0.9998282,0.00002861773,0.000008951496,0.0000280257,0.00003832705,0.00006781647],"domain_scores_gemma":[0.9997292,0.00007264054,0.00007645841,0.00001575042,0.00006573914,0.00004007676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000103575,0.0003108784,0.9630823,0.00008828068,0.0001166038,0.01025476,0.006628667,0.003104317,0.001647582,0.0007983017,0.001195966,0.01266868],"study_design_scores_gemma":[0.00001049665,0.00009807775,0.9626253,0.000020792,0.00006223597,0.001489094,0.02684473,0.004974115,0.0003828582,0.0001927743,0.003280688,0.00001876728],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999181,0.00004482968,0.00008023683,0.00004907882,0.000002126091,0.000008644315,0.0001619277,0.000003126747,0.0004690025],"genre_scores_gemma":[0.9991701,0.00009234529,0.0002369506,0.00001002326,0.000003238289,0.000006579889,0.0001818455,0.000001622402,0.0002973654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1108503,"threshold_uncertainty_score":0.2204101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03072617676860138,"score_gpt":0.200196762397767,"score_spread":0.1694705856291656,"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."}}