{"id":"W1989084537","doi":"10.1007/s00267-003-0142-y","title":"Application of Decision Analysis to Forest Road Deactivation in Unstable Terrain","year":2004,"lang":"en","type":"article","venue":"Environmental Management","topic":"Tree Root and Stability Studies","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Golder Associates (Canada)","funders":"","keywords":"Forest road; Cost–benefit analysis; Ranking (information retrieval); Decision analysis; Environmental resource management; Terrain; Resource (disambiguation); Computer science; Forest management; Liability; Adaptive management; Transport engineering; Business; Environmental science; Geography; Economics; Ecology; Engineering","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":[0.003621924,0.0007651552,0.001185168,0.002011623,0.001098924,0.001901075,0.000776543,0.0009044886,0.003943773],"category_scores_gemma":[0.0106409,0.0004181604,0.0008344384,0.001531169,0.001200246,0.001141195,0.0007855869,0.0009774282,0.0001705806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002084518,"about_ca_system_score_gemma":0.002647689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0238049,"about_ca_topic_score_gemma":0.01858976,"domain_scores_codex":[0.998389,0.001020071,0.00005762548,0.000103947,0.0002368727,0.0001925515],"domain_scores_gemma":[0.9873728,0.01156432,0.000290878,0.0001120867,0.0005402233,0.0001196851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002676949,0.0002235114,0.006343805,0.0001152167,0.000106017,0.0001801852,0.000260694,0.899626,0.001251902,0.03964897,0.0006437836,0.05133232],"study_design_scores_gemma":[0.00001614728,0.00006511626,0.0007197984,0.000007259629,0.00002372522,0.00001427384,0.0001464126,0.9872451,0.0004946838,0.01091552,0.0003407543,0.00001109064],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5287156,0.000536621,0.451015,0.0006626567,0.00007948852,0.0002585735,0.000216593,0.000157532,0.01835802],"genre_scores_gemma":[0.9673548,0.000185923,0.03052856,0.00002621136,0.00001733331,0.00006917605,0.00004585122,0.00002219765,0.001749977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0238049,"threshold_uncertainty_score":0.0473327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003000782810396415,"score_gpt":0.1867327278342156,"score_spread":0.1837319450238192,"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."}}