{"id":"W2168156523","doi":"10.1111/ele.12420","title":"Acceleration of cyanobacterial dominance in north temperate‐subarctic lakes during the Anthropocene","year":2015,"lang":"en","type":"article","venue":"Ecology Letters","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":384,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Ottawa; University of Regina; McGill University","funders":"Economic and Social Research Council; Engineering and Physical Sciences Research Council; Fundació Bosch i Gimpera; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Alberta Ingenuity Centre for Water Research","keywords":"Subarctic climate; Dominance (genetics); Temperate climate; Cyanobacteria; Ecology; Phytoplankton; Environmental science; Nutrient; Biomass (ecology); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000210113,0.00007803857,0.0001357559,0.0000184912,0.00006169543,0.000009850944,0.0001493116,0.00004039071,0.0002222788],"category_scores_gemma":[0.00003144866,0.00005861059,0.00001999334,0.0001295862,0.0001629368,0.0001214978,0.00005701765,0.00008144532,0.00007640353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001688505,"about_ca_system_score_gemma":0.00001188098,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003948892,"about_ca_topic_score_gemma":0.02917124,"domain_scores_codex":[0.9992793,0.00008864426,0.0002181553,0.0001473013,0.00008214256,0.0001844272],"domain_scores_gemma":[0.9996694,0.0000388254,0.0001035272,0.0001520972,0.000004648035,0.00003146446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002744491,0.00002619353,0.9825622,0.00000663337,0.000004514429,0.000007101406,0.0004610538,0.003968636,0.01275878,0.00001253007,0.0001314869,0.00003344907],"study_design_scores_gemma":[0.0004956617,0.0000370564,0.9968005,0.000003886491,0.000003969827,0.00000945362,0.00005560915,0.001244154,0.0011335,0.00001617553,0.0001294878,0.00007051571],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980987,0.00000272358,0.00002279871,0.001085228,0.0004045041,0.0001777026,0.000004646076,0.000006915754,0.0001967277],"genre_scores_gemma":[0.9995653,0.000004103429,0.00006981331,0.00025003,0.00005642378,0.00001523492,0.000005311436,0.000006004838,0.00002779521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02877635,"threshold_uncertainty_score":0.9885439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008894121199001633,"score_gpt":0.2059451587827256,"score_spread":0.1970510375837239,"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."}}