{"id":"W1586087568","doi":"10.1111/ddi.12356","title":"Conservation of future boreal forest bird communities considering lags in vegetation response to climate change: a modified refugia approach","year":2015,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Alberta Environment and Protected Areas; University of Alberta","funders":"Environment Canada; U.S. Fish and Wildlife Service; University of Alberta; Alberta Innovates - Technology Futures; Alberta Biodiversity Monitoring Institute; Natural Sciences and Engineering Research Council of Canada; Climate Change and Emissions Management Corporation","keywords":"Seral community; Climate change; Boreal; Ecology; Vegetation (pathology); Biome; Geography; Habitat; Baseline (sea); Environmental science; Ecoregion; Biodiversity; Ecosystem; Physical geography; Biology; Fishery","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":[],"consensus_categories":[],"category_scores_codex":[0.0003930164,0.00008894286,0.0001251872,0.00005343768,0.0003930372,0.00001955493,0.0001045934,0.00007035401,0.00006274792],"category_scores_gemma":[0.00005776252,0.00009534913,0.00002610443,0.0003153753,0.0001904688,0.000242444,0.0006370392,0.00008236656,0.00002270901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002855015,"about_ca_system_score_gemma":0.000008945844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003887981,"about_ca_topic_score_gemma":0.008525207,"domain_scores_codex":[0.9992725,0.0001077632,0.0001374788,0.0001241437,0.0001748653,0.0001833053],"domain_scores_gemma":[0.9995875,0.00004920013,0.00006009652,0.0001375985,0.00003954278,0.0001260514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000441413,0.0001433275,0.9773467,0.00002463996,0.000004841307,0.000002859115,0.007995298,0.0001005638,0.0001065074,0.01305205,0.0006327868,0.0001490359],"study_design_scores_gemma":[0.0006840465,0.00006160598,0.9780896,0.00001484357,0.00001278083,0.000003566915,0.01884677,0.0008507707,0.00004345315,0.0001876065,0.001098,0.0001069856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959946,0.00003080325,0.0003555218,0.001109788,0.00004927276,0.00022407,0.0004827616,0.00004100722,0.001712211],"genre_scores_gemma":[0.9992571,0.00004285619,0.0001052808,0.0001740412,0.00001021953,0.00001960888,0.0003828211,0.000003537756,0.00000450241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01286445,"threshold_uncertainty_score":0.5877491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.095093573786901,"score_gpt":0.260570520552603,"score_spread":0.165476946765702,"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."}}