{"id":"W2595664796","doi":"10.1002/ece3.2696","title":"Species distribution models predict temporal but not spatial variation in forest growth","year":2017,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Sixth Framework Programme; Seventh Framework Programme; Natural Sciences and Engineering Research Council of Canada; European Cooperation in Science and Technology; Alexander von Humboldt-Stiftung","keywords":"Scots pine; Species distribution; Habitat; Climate change; Dendrochronology; Forest inventory; Ecology; Physical geography; Beech; Occupancy; Breeding bird survey; Environmental science; Geography; Forest management; Pinus <genus>; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009734366,0.0004267179,0.0002463726,0.0006588246,0.000172085,0.0005696613,0.0004336505,0.0004255877,0.001078066],"category_scores_gemma":[0.002557164,0.000277757,0.000648785,0.000472801,0.0002545141,0.0009125386,0.0003088226,0.0003772493,0.0006247078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004734751,"about_ca_system_score_gemma":0.0002690412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008481397,"about_ca_topic_score_gemma":0.01677889,"domain_scores_codex":[0.9997702,0.00005888487,0.00001327152,0.000101083,0.00002662601,0.00002998606],"domain_scores_gemma":[0.9989437,0.000579046,0.0002194556,0.0001204962,0.00009944912,0.00003780823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006681569,0.00005168472,0.3674222,0.00004598105,0.0002268329,0.00006198169,0.0001664043,0.5996512,0.003763419,0.00227643,0.0009066779,0.02536047],"study_design_scores_gemma":[0.000007156327,0.00002525855,0.1342433,0.00001077813,0.00002985144,0.00009922345,0.00005285537,0.8608673,0.0005269399,0.00335987,0.0007632991,0.00001416476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.912213,0.0002098551,0.08261788,0.0002197755,0.00002048895,0.00002067282,0.001135899,0.0004033915,0.003159123],"genre_scores_gemma":[0.9949132,0.0000674387,0.004084496,0.000027377,0.000006587871,0.00001844711,0.0004798221,0.00002903608,0.0003734687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008481397,"threshold_uncertainty_score":0.01686406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176647827605853,"score_gpt":0.2214687938724584,"score_spread":0.1997023155963998,"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."}}