{"id":"W2161829879","doi":"10.4319/lo.2009.54.6_part_2.2283","title":"Lakes as sentinels of climate change","year":2009,"lang":"en","type":"article","venue":"Limnology and Oceanography","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":1925,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University; Ministry of the Environment, Conservation and Parks","funders":"Leibniz-Gemeinschaft; Strong; New York State Department of Environmental Conservation; Sveriges Lantbruksuniversitet; Andrew W. Mellon Foundation","keywords":"Climate change; Environmental science; Drainage basin; Eutrophication; Environmental change; Range (aeronautics); Physical geography; Ecology; Geography; 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":[0.002372112,0.0003396361,0.0005706079,0.001378211,0.0005404846,0.001460937,0.0004157077,0.0006494307,0.001142105],"category_scores_gemma":[0.003387215,0.0003837636,0.0002730934,0.001315365,0.0004472084,0.001579093,0.001651527,0.0005319868,0.0003241891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005361476,"about_ca_system_score_gemma":0.000528562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002546782,"about_ca_topic_score_gemma":0.004870515,"domain_scores_codex":[0.9987333,0.0006933389,0.00005677437,0.0001847711,0.0001677899,0.0001640099],"domain_scores_gemma":[0.997912,0.0008139171,0.0005695525,0.0001602886,0.0003107009,0.0002335176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001655225,0.0001922856,0.6000825,0.000709887,0.000543422,0.0005070987,0.004985082,0.01992968,0.1614408,0.01825324,0.0080832,0.1836176],"study_design_scores_gemma":[0.0001474956,0.001168375,0.6700657,0.0002415312,0.0005552446,0.0008919663,0.004479839,0.1612078,0.06065409,0.0272477,0.07299346,0.0003468666],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9247117,0.003612961,0.05465643,0.000935242,0.0001885124,0.000194877,0.002671518,0.0008246031,0.01220417],"genre_scores_gemma":[0.9683651,0.0005651384,0.02842606,0.0001511876,0.00008850956,0.0001011367,0.0008587497,0.00003580952,0.001408196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002546782,"threshold_uncertainty_score":0.01254511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007447425031599077,"score_gpt":0.2173410855984503,"score_spread":0.2098936605668512,"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."}}