{"id":"W3093007947","doi":"10.1073/pnas.2013181117","title":"Changing nutrient cycling in Lake Baikal, the world’s oldest lake","year":2020,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Water Resources and Management","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Natural Environment Research Council; Irkutsk State University; University College London; Siberian Branch, Russian Academy of Sciences; Research Councils UK; Sight Research UK","keywords":"Ecosystem; Biodiversity; Endemism; Climate change; Geography; Nutrient; Nutrient cycle; Ecology; Oceanography; Environmental science; Physical geography; Geology; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001775676,0.0001468891,0.0001794145,0.0006650834,0.0008905122,0.0006657423,0.0002670155,0.0003024978,0.0005810194],"category_scores_gemma":[0.0003740125,0.0001118069,0.0001041702,0.0008343434,0.0004469672,0.0007401279,0.0008020927,0.0002925726,0.00009292228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002319021,"about_ca_system_score_gemma":0.001347097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1800488,"about_ca_topic_score_gemma":0.3587273,"domain_scores_codex":[0.9999129,0.00001023052,0.000008462617,0.00002650045,0.00001936981,0.00002261701],"domain_scores_gemma":[0.9998612,0.000008366793,0.00005495113,0.00000571188,0.00003594649,0.00003367274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001437989,0.00006039801,0.9731785,0.00007509002,0.0001111187,0.0003439398,0.00167852,0.0003616143,0.01264528,0.0002122987,0.0006711899,0.0105181],"study_design_scores_gemma":[0.000004401186,0.0000175753,0.9982571,0.000007248403,0.00001463765,0.00007959754,0.0003582914,0.0003149465,0.0002897723,0.00005543439,0.0005935058,0.000007560832],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985418,0.000344801,0.00004159862,0.0001252083,0.000003514669,0.000002200497,0.0002917202,0.000005425796,0.00064358],"genre_scores_gemma":[0.9992266,0.000202562,0.0001294995,0.00004600421,0.000003806141,0.00000338148,0.0001965475,0.000001892432,0.000189722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1800488,"threshold_uncertainty_score":0.3580016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03574438588864886,"score_gpt":0.2621843066197675,"score_spread":0.2264399207311187,"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."}}