{"id":"W2552198296","doi":"10.1002/ecs2.1549","title":"Rapid latitudinal range expansion at cold limits unlikely for temperate understory forest plants","year":2016,"lang":"en","type":"article","venue":"Ecosphere","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Ministère des Forêts, de la Faune et des Parcs","keywords":"Range (aeronautics); Occupancy; Ecotone; Understory; Ecology; Microclimate; Abundance (ecology); Species distribution; Temperate climate; Environmental science; Temperate rainforest; Edaphic; Habitat; Niche; Boreal; Climate change; Taiga; Global warming; Physical geography; Geography; Ecosystem; Biology; Canopy","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001108329,0.0001433648,0.0001237577,0.000007499467,0.0001881988,0.00002421345,0.0001364136,0.00008544279,0.09927571],"category_scores_gemma":[0.00001726523,0.00009936482,0.00007765692,0.00006373264,0.0001045089,0.0001598994,0.00008634399,0.00004007814,0.01661706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008602819,"about_ca_system_score_gemma":0.000008981565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000028716,"about_ca_topic_score_gemma":0.0031311,"domain_scores_codex":[0.999042,0.00001747979,0.0001441374,0.0003040136,0.0001774826,0.0003148866],"domain_scores_gemma":[0.999583,0.00006437056,0.00004940411,0.0001788837,0.000007697854,0.0001166575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001020787,0.00005649493,0.01156366,0.00001871096,0.00001381389,0.000006717789,0.00008311472,0.00000541006,0.01918906,0.001422215,0.9650506,0.002488116],"study_design_scores_gemma":[0.001568613,0.0001845525,0.1398863,0.00006180697,0.000018098,0.000008598895,0.0003994507,0.000067571,0.008613397,0.0002175827,0.8486487,0.0003253408],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.940428,0.0004427049,0.0001416729,0.0009949487,0.0004333449,0.0003312719,0.0003043714,0.00009435132,0.05682932],"genre_scores_gemma":[0.9807848,0.0003311179,0.00004992067,0.0002850213,0.00007162417,0.00006894175,0.00003355027,0.00002235235,0.01835265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1283227,"threshold_uncertainty_score":0.9841486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04497196714116131,"score_gpt":0.2357635068537402,"score_spread":0.1907915397125789,"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."}}