{"id":"W2954282842","doi":"10.5539/jas.v11n11p172","title":"Application of the Markov Chain in Macroeconomic Analysis of a Managed Forest in the Amazon","year":2019,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Agricultural and Food Sciences","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Empresa Brasileira de Pesquisa Agropecuária; Universidade Federal do Acre","keywords":"Markov chain; Amazon rainforest; Valuation (finance); Economics; Stumpage; Econometrics; Agricultural economics; Geography; Forestry; Environmental science; Statistics; Mathematics; Ecology; Accounting","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00130791,0.0002279448,0.0003809963,0.0007655519,0.0003513463,0.0008098678,0.000281195,0.0003084454,0.001245935],"category_scores_gemma":[0.004548838,0.0001873791,0.0005847901,0.0005076192,0.0004118228,0.0005894689,0.0005394259,0.0003835844,0.00006271785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009403335,"about_ca_system_score_gemma":0.001494263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03612233,"about_ca_topic_score_gemma":0.0205192,"domain_scores_codex":[0.9996612,0.0001575389,0.00001846272,0.00006144951,0.00004268919,0.00005869893],"domain_scores_gemma":[0.9984092,0.001127763,0.0002080512,0.00006030656,0.0001261963,0.00006851384],"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":[0.00007170304,0.00004340851,0.03749522,0.00003181988,0.00008453189,0.0001618598,0.00009791592,0.9281428,0.0006748615,0.02464304,0.0002330708,0.008319747],"study_design_scores_gemma":[0.000003325958,0.00001223899,0.003542052,0.000004936833,0.000008569195,0.00001103675,0.00002430592,0.991739,0.00008098367,0.00446497,0.0001032292,0.000005201069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8071049,0.0004437281,0.1880333,0.0005648267,0.0000402777,0.00006865917,0.0004575139,0.00009631648,0.003190432],"genre_scores_gemma":[0.9925814,0.0001572432,0.006668328,0.00001099227,0.00001334286,0.00002992516,0.0001559335,0.000005988029,0.0003768105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03612233,"threshold_uncertainty_score":0.07182413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007164131215903459,"score_gpt":0.2004956043812592,"score_spread":0.1933314731653557,"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."}}