{"id":"W2638942861","doi":"10.3390/w9060442","title":"Transparency, Geomorphology and Mixing Regime Explain Variability in Trends in Lake Temperature and Stratification across Northeastern North America (1975–2014)","year":2017,"lang":"en","type":"article","venue":"Water","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Ministry of the Environment, Conservation and Parks; Toronto Metropolitan University","funders":"Division of Emerging Frontiers; National Institute of Food and Agriculture; Global Lake Ecological Observatory Network; Natural Sciences and Engineering Research Council of Canada; Colby College; U.S. Department of Agriculture; University of Miami; State University of New York Oneonta; New York State Department of Environmental Conservation; State University of New York; National Science Foundation","keywords":"Stratification (seeds); Climate change; Thermal stratification; Water column; Environmental science; Hypolimnion; Lake ecosystem; Ecosystem; Global warming; Surface water; Oceanography; Hydrology (agriculture); Ecology; Geology; Eutrophication; Thermocline","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005553878,0.0001983699,0.0001409597,0.000397469,0.0004441316,0.0003721064,0.0001961032,0.000178902,0.001524548],"category_scores_gemma":[0.001520237,0.0001567072,0.0004084366,0.0005214867,0.0003028538,0.0003893991,0.0005968997,0.0002168259,0.0001539787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006114164,"about_ca_system_score_gemma":0.0005264071,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1136937,"about_ca_topic_score_gemma":0.2546713,"domain_scores_codex":[0.9998395,0.00004056413,0.00001436882,0.00005324671,0.00002342512,0.00002875602],"domain_scores_gemma":[0.9992841,0.0001517001,0.0002712439,0.00006225368,0.0001346235,0.00009617262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002108203,0.000008181879,0.9961832,0.000009290757,0.00008232469,0.00002160258,0.0002483043,0.0002099668,0.0003416699,0.00003957742,0.0003233277,0.002511337],"study_design_scores_gemma":[6.106143e-7,0.000002338132,0.9992198,0.000003234234,0.00001005842,0.000005862912,0.0001015585,0.0004205225,0.00001573354,0.00002744999,0.0001915002,0.000001225852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982923,0.0003428147,0.0002314927,0.0001427883,0.000006996582,0.000004027504,0.0003480857,0.00001273582,0.000618784],"genre_scores_gemma":[0.9993911,0.00006490359,0.0001212126,0.00001980577,0.000004367604,0.000002927889,0.0002221629,0.000003155169,0.0001704246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8863063,"threshold_uncertainty_score":0.2260638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01309097858453553,"score_gpt":0.2249383603291046,"score_spread":0.2118473817445691,"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."}}