{"id":"W2373685876","doi":"","title":"Dynamic Change of Land Use & Landscape Pattern in Middle and Lower Reaches of Shule River During Recent 35 Years","year":2014,"lang":"en","type":"article","venue":"Soils","topic":"Environmental Changes in China","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Grassland; Geography; Land use; Land cover; Cultivated land; Fragmentation (computing); Physical geography; Land use, land-use change and forestry; Driving factors; Diversity index; Landscape ecology; Population growth; Population; Forestry; Ecology; China; Demography; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001307967,0.00007734411,0.00009946542,0.0006118981,0.0002001804,0.0002902306,0.0001197655,0.0001319354,0.0005652649],"category_scores_gemma":[0.0002180821,0.00008562359,0.0001764057,0.001003399,0.0001879287,0.0002355763,0.0002802823,0.00008825687,0.00005544857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004408924,"about_ca_system_score_gemma":0.000301796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03179385,"about_ca_topic_score_gemma":0.108498,"domain_scores_codex":[0.9999171,0.0000110747,0.000008871129,0.00002286353,0.00001537663,0.00002467556],"domain_scores_gemma":[0.9998784,0.00001740659,0.00004229675,0.000006535557,0.00002542726,0.00002993222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002032588,0.00001142336,0.9934476,0.00001569557,0.00002321037,0.0001809395,0.0005792719,0.0002606318,0.001068438,0.00008192506,0.0001046883,0.004205916],"study_design_scores_gemma":[4.267064e-7,0.000007087258,0.9991593,0.000001488542,0.000003802287,0.00002859632,0.0002813745,0.0003065526,0.00004482764,0.000008763523,0.0001564406,0.000001381648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997003,0.00002736567,0.00002686644,0.000006932706,3.12182e-7,0.000001311563,0.00009602997,0.000001681144,0.000139161],"genre_scores_gemma":[0.9995471,0.0000233646,0.00004321536,0.000002544866,4.922478e-7,0.000002633319,0.0001978297,3.049667e-7,0.000182494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03179385,"threshold_uncertainty_score":0.06321752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02239661549059338,"score_gpt":0.213712629653608,"score_spread":0.1913160141630146,"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."}}