{"id":"W2939608414","doi":"10.1139/cjfr-2018-0532","title":"Optimal forest management under financial risk aversion with discounted Markov decision process models","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Forest Service; National Institute of Food and Agriculture; Purdue University; U.S. Department of Agriculture","keywords":"Variance (accounting); Risk aversion (psychology); Economics; Econometrics; Net present value; Markov decision process; Mathematics; Actuarial science; Expected utility hypothesis; Statistics; Markov process; Financial economics; Microeconomics; Production (economics)","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":[0.003284747,0.001168327,0.001724999,0.0007686122,0.0006375831,0.002369588,0.001257917,0.001586707,0.002154744],"category_scores_gemma":[0.00696433,0.0009556231,0.001177217,0.0007123995,0.001765223,0.001957736,0.001765923,0.001994617,0.0001821364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00365557,"about_ca_system_score_gemma":0.004143244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02189783,"about_ca_topic_score_gemma":0.01700354,"domain_scores_codex":[0.9985142,0.0007541274,0.00004656825,0.0001980585,0.0001955118,0.0002914758],"domain_scores_gemma":[0.9970229,0.002139933,0.0003774477,0.00006219153,0.0001986892,0.0001987927],"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":[0.00004043496,0.00001874744,0.0002999055,0.00002353432,0.00001991259,0.00003596254,0.00002896546,0.9622846,0.0001424045,0.03499029,0.0002113303,0.001903884],"study_design_scores_gemma":[0.00001372211,0.00001499484,0.00008086383,0.000006154562,0.000008329863,0.000005712639,0.000009224706,0.9731296,0.0000409163,0.02655623,0.0001258721,0.000008496705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.107815,0.001050052,0.8785856,0.00147564,0.00009967192,0.00009889437,0.0002299183,0.0001656678,0.01047959],"genre_scores_gemma":[0.9622431,0.0007408891,0.03059119,0.0001360222,0.00006495845,0.0001296002,0.0001017596,0.00003748448,0.005955037],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02189783,"threshold_uncertainty_score":0.04354072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169070564335226,"score_gpt":0.2790913637501858,"score_spread":0.2621843073166633,"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."}}