{"id":"W2735175783","doi":"10.5558/tfc2017-019","title":"The NEBIE plot network: Highlights of long-term scientific studies","year":2017,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"BioForest Technologies (Canada); Manitoba Environmental Industries Association; Ministry of Natural Resources and Forestry; Ontario Forest Research Institute; Université du Québec à Montréal; Lakehead University; University of Guelph","funders":"University of Waterloo; FPInnovations; Lakehead University; Ontario Innovation Trust; Canadian Forest Service; Ontario Ministry of Natural Resources and Forestry; Natural Resources Canada; Ministry of Natural Resources; Natural Sciences and Engineering Research Council of Canada; U.S. Forest Service; University of Pittsburgh","keywords":"Silviculture; Forest management; Environmental science; Temperate rainforest; Taiga; Boreal; Environmental resource management; Agroforestry; Forest ecology; Productivity; Scale (ratio); Geography; Forestry; Temperate climate; Ecology; Ecosystem; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.09959375,0.0008548142,0.001343456,0.008611003,0.003235457,0.009832229,0.003982843,0.003275132,0.008273542],"category_scores_gemma":[0.0713998,0.000444538,0.0007872097,0.01663455,0.00165067,0.00727666,0.005960987,0.002955175,0.002188796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01258394,"about_ca_system_score_gemma":0.04337982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04042782,"about_ca_topic_score_gemma":0.1204569,"domain_scores_codex":[0.9756656,0.008897983,0.003407049,0.001488783,0.008678555,0.001862035],"domain_scores_gemma":[0.7910305,0.06239739,0.01915536,0.01073159,0.08882694,0.02785822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001410535,0.0005007276,0.01117387,0.01772128,0.0001911246,0.0003541943,0.001540013,0.0008107678,0.002951338,0.01887589,0.4278568,0.5166134],"study_design_scores_gemma":[0.0000738953,0.0002530486,0.02123572,0.008784002,0.00008214925,0.0001186318,0.001221701,0.0002577894,0.0005546769,0.002923222,0.9644424,0.000052698],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.008256217,0.7768221,0.006836979,0.1322557,0.02497069,0.001615211,0.01271421,0.0004230788,0.03610588],"genre_scores_gemma":[0.09509024,0.6533135,0.07573526,0.05335006,0.03982054,0.005386894,0.03616069,0.0006429048,0.04049998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09959375,"threshold_uncertainty_score":0.5267084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05206861580817186,"score_gpt":0.2636406864035522,"score_spread":0.2115720705953804,"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."}}