{"id":"W4400839958","doi":"10.1002/eap.3011","title":"Functional responses of understory plants to natural disturbance‐based management in eastern and western Canada","year":2024,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service; University of Alberta; Université du Québec à Montréal; Université du Québec en Abitibi-Témiscamingue","funders":"Canadian Forest Service; Forest Resource Improvement Association of Alberta; Fondation de l’Université du Québec en Abitibi-Témiscamingue; Natural Sciences and Engineering Research Council of Canada; U.S. Forest Service; Natural Resources Canada; University of Alberta; Weyerhaeuser Company","keywords":"Understory; Species richness; Ecology; Biodiversity; Disturbance (geology); Vegetation (pathology); Forest management; Biology; Species diversity; Plant community; Taiga; Geography; Canopy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007604351,0.00005440905,0.00006790733,0.00002885131,0.00006547551,0.000005421149,0.00006200265,0.00002346352,0.0001299788],"category_scores_gemma":[0.000006553406,0.00004559245,0.00001031911,0.0001184775,0.00009328218,0.00002472673,0.00007993605,0.00006267431,0.00004927778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001694479,"about_ca_system_score_gemma":0.00001640992,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001508269,"about_ca_topic_score_gemma":0.3108617,"domain_scores_codex":[0.9995016,0.00002240746,0.0001111639,0.0001895075,0.00007979838,0.00009546478],"domain_scores_gemma":[0.9996946,0.0001929775,0.00001599878,0.00006234894,0.000002622167,0.00003147683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006795018,0.0001886909,0.9788092,0.00004439749,0.00003617121,0.00002317689,0.0001244206,0.004247684,0.0001389169,0.00646939,0.004532652,0.00531735],"study_design_scores_gemma":[0.00008058907,0.00002008909,0.9895232,0.000005704886,0.000004422884,9.605606e-7,0.00006825544,0.001784799,0.000005848885,0.0008078914,0.007645146,0.0000530776],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909694,0.0001739305,0.003084896,0.002767874,0.00009293234,0.0003644792,0.00002482146,0.00002087259,0.002500777],"genre_scores_gemma":[0.996914,0.0000108599,0.0004055938,0.0005086505,0.000006319755,0.000268586,0.000009615381,0.000002236047,0.001874129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3093534,"threshold_uncertainty_score":0.7017133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.017758382492883,"score_gpt":0.2453646444290374,"score_spread":0.2276062619361544,"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."}}