{"id":"W2976700241","doi":"10.1111/ddi.12990","title":"Antagonistic, synergistic and direct effects of land use and climate on Prairie wetland ecosystems: Ghosts of the past or present?","year":2019,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Global Institute for Water Security; Ducks Unlimited Canada; University of Alberta; University of Saskatchewan; Wildlife Conservation Society Canada","funders":"Environment and Climate Change Canada; Mitacs; Government of Canada; Alberta Biodiversity Monitoring Institute","keywords":"Wetland; Ecology; Abundance (ecology); Species richness; Environmental science; Biodiversity; Climate change; Ecosystem; Grassland; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001201776,0.0002078308,0.0003802231,0.0003784048,0.0005117925,0.001067312,0.0003457472,0.0004272806,0.001635313],"category_scores_gemma":[0.001446639,0.0002217995,0.0003328298,0.0003225798,0.0009216505,0.0007073929,0.0008079939,0.0003757293,0.00009144934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000538684,"about_ca_system_score_gemma":0.0005577304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01420494,"about_ca_topic_score_gemma":0.05591101,"domain_scores_codex":[0.9995721,0.0001873995,0.00001805046,0.000082194,0.00005674624,0.00008362751],"domain_scores_gemma":[0.9983001,0.0005145833,0.0003938049,0.0001118842,0.0001681942,0.0005114457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005725985,0.0001601035,0.9751734,0.00008038471,0.0005224627,0.0001038795,0.0006210596,0.0002822537,0.009994652,0.0004676599,0.0003725878,0.01164905],"study_design_scores_gemma":[0.000004468079,0.00006929262,0.9983669,0.000007063736,0.00005810718,0.00004218531,0.0005662793,0.0003792677,0.0001094171,0.0001370712,0.0002528281,0.00000714572],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980732,0.0007569312,0.00009836831,0.0002528975,0.000007318375,0.000003596033,0.00005582117,0.000003597724,0.0007481259],"genre_scores_gemma":[0.9994405,0.0001666497,0.0001013164,0.00006534617,0.00001050642,0.000001580801,0.00003629913,0.000001656265,0.0001762046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01420494,"threshold_uncertainty_score":0.02824455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01718446545897849,"score_gpt":0.214258496578414,"score_spread":0.1970740311194355,"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."}}