{"id":"W2019825912","doi":"10.1080/10402381.2013.865687","title":"Insights for lake management gained when paleolimnological and water column monitoring studies are combined: A case study from Baptiste Lake","year":2013,"lang":"en","type":"article","venue":"Lake and Reservoir Management","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Environment and Protected Areas; Queen's University; McGill University","funders":"","keywords":"Eutrophication; Diatom; Environmental science; Paleolimnology; Watershed; Water quality; Water column; Hydrology (agriculture); Nutrient; Ecology; Boreal; Oceanography; Geology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002196747,0.0002799437,0.0003851574,0.00005040626,0.0004350868,0.0001616183,0.0002023666,0.00006979816,0.0002705375],"category_scores_gemma":[0.000006010571,0.0001868468,0.00004667091,0.00006941817,0.0001204215,0.0001914982,0.001063509,0.0001007105,0.0000610915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000348373,"about_ca_system_score_gemma":7.270268e-7,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003714395,"about_ca_topic_score_gemma":0.07492676,"domain_scores_codex":[0.9982473,0.00008825096,0.0003822889,0.0006101695,0.0002837769,0.0003881793],"domain_scores_gemma":[0.9992555,0.00008541122,0.00009911334,0.0004052212,0.00001902206,0.0001356861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001485555,0.0008975974,0.9667813,0.0009356704,0.0017056,0.004773423,0.009036977,0.0007623133,0.00002619142,0.0006295405,0.007108523,0.007194343],"study_design_scores_gemma":[0.008459834,0.001465512,0.7550973,0.0004358875,0.0007067558,0.00007028946,0.09670098,0.01016246,0.00002193082,0.01727148,0.1082129,0.001394722],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994364,0.0002504863,0.0001631677,0.0003936589,0.0002321459,0.002778065,0.00003895512,0.00005460269,0.001724924],"genre_scores_gemma":[0.9918528,0.0003060827,0.001699775,0.0001035506,0.00006770674,0.0009055542,0.00003095156,0.00002034371,0.005013278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.211684,"threshold_uncertainty_score":0.9419534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02601433012217732,"score_gpt":0.2456816023862286,"score_spread":0.2196672722640513,"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."}}