{"id":"W4396826285","doi":"10.1139/er-2023-0130","title":"Restoring forest ecosystem services through trait-based ecology","year":2024,"lang":"en","type":"article","venue":"Environmental Reviews","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais; Carleton University; McGill University; Natural Resources Canada; University of Alberta; Université Laval; Université du Québec à Montréal; Northern Alberta Institute of Technology; Canadian Forest Service","funders":"Canadian Forest Service; Office of Energy Research and Development","keywords":"Ecology; Trait; Ecosystem; Ecosystem services; Forest ecology; Environmental resource management; Biodiversity; Geography; Agroforestry; Environmental science; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003981278,0.0002720299,0.0002830687,0.00004128107,0.0001333843,0.00007056697,0.000383599,0.00007956887,0.007322736],"category_scores_gemma":[0.000005704134,0.0002240372,0.0001884204,0.0001805857,0.0001029684,0.0004171212,0.0001988157,0.0001579792,0.03377508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003863117,"about_ca_system_score_gemma":0.00000426645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001819963,"about_ca_topic_score_gemma":0.000661282,"domain_scores_codex":[0.9982816,0.0001163909,0.0004058314,0.0005133405,0.0002734685,0.0004093692],"domain_scores_gemma":[0.9993357,0.00004955469,0.00008272092,0.0004334198,9.708282e-8,0.00009851512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008368826,0.0009089244,0.3894439,0.003931468,0.00020972,0.0005408541,0.004804763,0.005504077,0.01149057,0.004102345,0.2663359,0.3126438],"study_design_scores_gemma":[0.0001320774,0.00007167772,0.01633794,0.000146714,0.0000394336,0.000006525833,0.00001478552,0.003080846,0.00007336316,0.0001670006,0.9796898,0.0002398183],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8646798,0.01465332,0.0002482659,0.0009653531,0.001398499,0.001944154,0.00004710033,0.0003215513,0.1157419],"genre_scores_gemma":[0.9862324,0.002502554,0.001160731,0.001099323,0.0002333825,0.0001955049,0.0000751434,0.00005271809,0.00844827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7133539,"threshold_uncertainty_score":0.9935847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01736910612756096,"score_gpt":0.2549316686214512,"score_spread":0.2375625624938902,"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."}}