{"id":"W2489684014","doi":"10.1111/1365-2664.12742","title":"Extreme climate events counteract the effects of climate and land‐use changes in <scp>A</scp>lpine tree lines","year":2016,"lang":"en","type":"article","venue":"Journal of Applied Ecology","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"European Research Council; Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig","keywords":"Ecotone; Climate change; Land use, land-use change and forestry; Ecosystem; Ecology; Grassland; Biodiversity; Global warming; Land use; Environmental science; Vegetation (pathology); Effects of global warming; Geography; Agroforestry; Habitat; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0003197025,0.0002498006,0.0002507905,0.0001750956,0.000262681,0.0007222043,0.0004807711,0.000319814,0.001266106],"category_scores_gemma":[0.0005958788,0.000119239,0.0004347936,0.0001700889,0.0002661361,0.0004494658,0.0003718043,0.0002549785,0.0001175121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000973632,"about_ca_system_score_gemma":0.0004810409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02614762,"about_ca_topic_score_gemma":0.0207857,"domain_scores_codex":[0.9998491,0.00005377765,0.000009086705,0.0000421409,0.00001465543,0.00003125917],"domain_scores_gemma":[0.999619,0.000103471,0.0001041096,0.00003628851,0.00005881305,0.00007819713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000488517,0.0003778944,0.4332685,0.0001984241,0.0004889325,0.0003464291,0.0003343778,0.4866019,0.05641871,0.003119085,0.001513348,0.01684385],"study_design_scores_gemma":[0.00007210684,0.0003252927,0.3989066,0.00001883534,0.0001140867,0.0001061606,0.000389615,0.5928916,0.003804024,0.001449424,0.00188259,0.00003966718],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979265,0.00003745269,0.001123738,0.0000591905,0.000003403856,0.000004940185,0.0001690583,0.00003304463,0.0006426018],"genre_scores_gemma":[0.9994829,0.00001500641,0.0002922698,0.00001729103,0.000001785109,0.00000435154,0.0001102469,0.000004339083,0.00007188603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02614762,"threshold_uncertainty_score":0.05199081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008964037884466215,"score_gpt":0.2262545001609594,"score_spread":0.2172904622764932,"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."}}