{"id":"W1986370534","doi":"10.1111/gcb.12321","title":"Linking climate change to population cycles of hares and lynx","year":2013,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Chinese Academy of Sciences","keywords":"North Atlantic oscillation; Predation; Climate change; Population; Ecology; Snow; Boreal; Environmental science; Population density; Taiga; Arctic oscillation; Geography; Snowshoe hare; Climatology; Density dependence; Physical geography; Biology; Northern Hemisphere; Demography; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005598704,0.0002380544,0.0002089596,0.0003488964,0.0003511961,0.0007234528,0.0003064598,0.0004438423,0.0007983236],"category_scores_gemma":[0.001821392,0.0002423518,0.0005827281,0.0003222951,0.0003478966,0.0004599822,0.0005211775,0.0003866212,0.00007757116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005152131,"about_ca_system_score_gemma":0.0004546424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01798091,"about_ca_topic_score_gemma":0.01512819,"domain_scores_codex":[0.9998372,0.00005407782,0.00000911682,0.00005894905,0.00001311603,0.0000275597],"domain_scores_gemma":[0.9996256,0.0001681352,0.00008485498,0.00003107143,0.00004090718,0.00004952895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001323329,0.0001330452,0.6478049,0.00003571048,0.0002719773,0.0002486031,0.0002193577,0.3382213,0.002994637,0.00239099,0.0007002112,0.006846881],"study_design_scores_gemma":[0.00003393947,0.0001195485,0.2412266,0.00001335647,0.0001192402,0.0000966721,0.0002914268,0.7544365,0.000538404,0.002191874,0.0008964268,0.00003590806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981226,0.00006483995,0.001252892,0.00007337764,0.00001060561,0.000004619674,0.0001469446,0.00001586552,0.0003081569],"genre_scores_gemma":[0.9993545,0.00005767972,0.0003080061,0.00001482768,0.000004845462,0.000005368504,0.0001494028,0.000004530712,0.0001006829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01798091,"threshold_uncertainty_score":0.03575248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0539248567996965,"score_gpt":0.3049532127592883,"score_spread":0.2510283559595918,"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."}}