{"id":"W4281609004","doi":"10.1007/s10342-022-01465-5","title":"Clear-cutting without additional regeneration treatments can trigger successional setbacks prolonging the expected time to compositional recovery in boreal forests","year":2022,"lang":"en","type":"article","venue":"European Journal of Forest Research","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi; Université Laval; Ministère des Ressources naturelles et des Forêts","funders":"Ministère des Forêts, de la Faune et des Parcs","keywords":"Ecological succession; Taiga; Boreal; Regeneration (biology); Ecology; Climate change; Sustainability; Clearcutting; Secondary succession; Agroforestry; Environmental science; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002233816,0.0001056695,0.0001537733,0.0001114472,0.001559807,0.0000698852,0.0004438533,0.00002176586,0.003015341],"category_scores_gemma":[0.0001881633,0.00004347386,0.00009467378,0.0005488884,0.0001333292,0.0001277957,0.0003557849,0.0005505651,0.00008154796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002042783,"about_ca_system_score_gemma":0.00005980546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005194216,"about_ca_topic_score_gemma":0.0003799398,"domain_scores_codex":[0.9968595,0.001504627,0.0003163611,0.0001956157,0.0007789836,0.0003449169],"domain_scores_gemma":[0.9989082,0.0005406265,0.0001546577,0.00004518293,0.0002494098,0.0001019139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004238154,0.0009166884,0.71503,0.000006963365,0.0002269901,0.001063152,0.001103303,0.00520451,0.002935996,0.0001358166,0.2411192,0.0280193],"study_design_scores_gemma":[0.0004233232,0.001832754,0.9884014,0.00003334426,0.000006306251,0.0001209966,0.0003345327,0.00008872127,0.00004676419,0.0001600151,0.008467942,0.00008392687],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878532,0.00004298367,9.760923e-7,0.009666374,0.00006919465,0.0002347706,0.0004373661,0.000008437395,0.00168667],"genre_scores_gemma":[0.9979762,0.000006646259,0.00009429373,0.0001827848,0.0003527676,0.00001707347,0.0004125007,0.000001990924,0.0009556919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2733714,"threshold_uncertainty_score":0.99974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03666456192300183,"score_gpt":0.2693454919154356,"score_spread":0.2326809299924338,"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."}}