{"id":"W3122297281","doi":"10.22004/ag.econ.18154","title":"MODELING ALTERNATIVE ZONING STRATEGIES IN FOREST MANAGEMENT","year":2004,"lang":"en","type":"preprint","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Forest Service; Natural Sciences and Engineering Research Council of Canada; U.S. Forest Service","keywords":"Zoning; Production (economics); Silviculture; Wood production; Forest management; Offset (computer science); Natural resource economics; Business; Triad (sociology); Environmental resource management; Pairwise comparison; Economics; Geography; Forestry; Computer science; Engineering; Civil engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001658149,0.0008546778,0.0007779277,0.001139519,0.0007821476,0.002497175,0.001445372,0.002702218,0.01050712],"category_scores_gemma":[0.004614966,0.0006155273,0.000737921,0.001433846,0.001571052,0.002302553,0.001377958,0.001308054,0.0003600132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004118676,"about_ca_system_score_gemma":0.001836254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04756548,"about_ca_topic_score_gemma":0.04644446,"domain_scores_codex":[0.9993377,0.0003496954,0.00001853835,0.00007840794,0.00005170906,0.0001638747],"domain_scores_gemma":[0.9985328,0.0009988873,0.000211654,0.00004124647,0.00009791883,0.0001174691],"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":[0.0000270912,0.00002735064,0.0003905474,0.00002021724,0.00001420156,0.00002974893,0.00003615046,0.966758,0.00008899287,0.03066948,0.0003108344,0.001627489],"study_design_scores_gemma":[0.00002657119,0.00002482236,0.0001890457,0.000009408701,0.00001095702,0.000006334149,0.00008090015,0.9800466,0.00003052515,0.01866296,0.0009050883,0.000006780208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.566519,0.003167285,0.355711,0.003630835,0.0001874425,0.0004423737,0.001371414,0.0003303569,0.06864016],"genre_scores_gemma":[0.9658996,0.0008736728,0.02086859,0.0001005866,0.0000295046,0.0002061147,0.0001625668,0.00003877205,0.01182054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04756548,"threshold_uncertainty_score":0.09457725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0322011302921785,"score_gpt":0.2531397067312153,"score_spread":0.2209385764390368,"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."}}