{"id":"W2037238618","doi":"10.1007/s10818-011-9123-z","title":"Land-use changes, forest/soil conditions and carbon sequestration dynamics: A bio-economic model at watershed level in Nepal","year":2011,"lang":"en","type":"article","venue":"Journal of Bioeconomics","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Carbon sequestration; Present value; Economics; Net present value; Clearing; Agricultural economics; Watershed; Land use; Natural resource economics; Agriculture; Biomass (ecology); Environmental science; Geography; Ecology; Production (economics)","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":[0.0007775905,0.0005220071,0.001003637,0.000744727,0.001277797,0.003376404,0.00203197,0.002772214,0.004826892],"category_scores_gemma":[0.001993839,0.0007320358,0.0009239031,0.001077845,0.001785179,0.002134108,0.001427296,0.001776256,0.0003594251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004606648,"about_ca_system_score_gemma":0.003053578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1429909,"about_ca_topic_score_gemma":0.1170548,"domain_scores_codex":[0.9997274,0.00012476,0.00001066447,0.00004087391,0.00001201522,0.00008423246],"domain_scores_gemma":[0.9989327,0.0006548233,0.0001087582,0.00003085925,0.00009841078,0.0001745568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002330305,0.0002847252,0.01513082,0.0000556826,0.0001272481,0.0008439816,0.0002220329,0.9611592,0.0004385196,0.0180634,0.0008754474,0.002565922],"study_design_scores_gemma":[0.00008601046,0.00009725335,0.005150893,0.00001455578,0.0001120641,0.00008883539,0.0004622318,0.9871302,0.0001455886,0.006034366,0.0006427048,0.00003539004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844003,0.0002036712,0.003168005,0.001495513,0.00001596578,0.00003800576,0.0006384418,0.00004725614,0.009992844],"genre_scores_gemma":[0.9952254,0.0001568647,0.000465509,0.00006437421,0.000007911517,0.00003322016,0.0001448822,0.000009455437,0.003892301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1429909,"threshold_uncertainty_score":0.2843172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04689673196274052,"score_gpt":0.2048848155022595,"score_spread":0.157988083539519,"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."}}