{"id":"W3083564138","doi":"10.1111/jvs.12945","title":"From delayed succession to alternative successional trajectory: How different moose browsing pressures contribute to forest dynamics following clear‐cutting","year":2020,"lang":"en","type":"article","venue":"Journal of Vegetation Science","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval; Center for Northern Studies","funders":"Fonds de recherche du Québec – Nature et technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Ecological succession; Plant community; Ecology; Disturbance (geology); Taiga; Abundance (ecology); Ecosystem; Regeneration (biology); Environmental science; Clearcutting; Balsam; Canopy; Biology; Botany","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":[0.0007160528,0.0001732344,0.000304298,0.0001441748,0.0005532313,0.0001839216,0.000622756,0.00004989082,0.00002987206],"category_scores_gemma":[0.001013972,0.0001370356,0.0001118309,0.0006671092,0.0001725324,0.001173968,0.0003029771,0.0002435177,0.0000247904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003424598,"about_ca_system_score_gemma":0.00006000237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006119408,"about_ca_topic_score_gemma":0.0005263889,"domain_scores_codex":[0.9976931,0.0001124627,0.0004504436,0.000374475,0.001039779,0.0003297183],"domain_scores_gemma":[0.9984828,0.0003397758,0.0004898931,0.0001030561,0.000154566,0.0004299167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003624904,0.0001134494,0.5632753,0.00001366869,0.00009613577,0.00006111472,0.01278095,0.3669333,0.04937514,0.0003107602,0.0002362281,0.006441376],"study_design_scores_gemma":[0.0007055642,0.0004761174,0.7798698,0.0001549717,0.00005340634,0.000005423391,0.0008514926,0.2133868,0.003094459,0.001116578,0.00005610388,0.0002292962],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9000996,0.0000486404,0.09100037,0.007749791,0.0005955887,0.000188331,0.00000770149,0.00001485244,0.0002951324],"genre_scores_gemma":[0.9922569,0.00000511128,0.006433978,0.001119711,0.0001397431,0.000005296724,0.000002988255,0.00001051787,0.00002569122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2165945,"threshold_uncertainty_score":0.5588148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0156360802135432,"score_gpt":0.279020044002776,"score_spread":0.2633839637892328,"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."}}