{"id":"W2029705307","doi":"10.1139/x05-283","title":"Evaluation of a large-scale forest scenario model in heterogeneous forests: a case study for Switzerland","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Forest Service; European Commission; Kanton Bern","keywords":"Initialization; Environmental science; Forest management; Stock (firearms); Carbon stock; Scale (ratio); Forest inventory; Estimation; Geography; Physical geography; Environmental resource management; Climate change; Ecology; Computer science; Agroforestry; Cartography","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":[0.001938942,0.001080917,0.0005977212,0.0005693234,0.000619345,0.000900647,0.001046353,0.00105805,0.001309631],"category_scores_gemma":[0.002652007,0.0002690887,0.0006398113,0.0007675721,0.0005561991,0.0007569881,0.000496215,0.0006650042,0.0001199645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001821473,"about_ca_system_score_gemma":0.0009409524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07871029,"about_ca_topic_score_gemma":0.06113394,"domain_scores_codex":[0.9994312,0.0003513652,0.00002310137,0.00006085952,0.00005744002,0.00007595762],"domain_scores_gemma":[0.9979451,0.00144296,0.0001086106,0.0001106987,0.0002733231,0.0001192572],"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":[0.0001472668,0.0001273455,0.005537552,0.00002644569,0.00002585095,0.0002187869,0.00003189996,0.9912803,0.0005583864,0.0003856923,0.0001850255,0.001475534],"study_design_scores_gemma":[0.00008351294,0.0001722697,0.004199971,0.000007812563,0.0000242756,0.00002457438,0.000078297,0.9941338,0.0008001545,0.000228515,0.000231721,0.00001523262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936186,0.00005171477,0.003302569,0.0001080958,0.0000105411,0.00007267513,0.0004487362,0.0001204969,0.002266689],"genre_scores_gemma":[0.9963174,0.00003705909,0.002757611,0.00001448601,0.000003944342,0.00004455883,0.0004373773,0.00001946408,0.0003680461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07871029,"threshold_uncertainty_score":0.1565043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05438950254216393,"score_gpt":0.3416111848361248,"score_spread":0.2872216822939609,"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."}}