{"id":"W2969802770","doi":"10.1002/lol2.10117","title":"Hot tops, cold bottoms: Synergistic climate warming and shielding effects increase carbon burial in lakes","year":2019,"lang":"en","type":"article","venue":"Limnology and Oceanography Letters","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":140,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Global warming; Environmental science; Climate change; Greenhouse gas; Ecosystem; Carbon cycle; Eutrophication; Greenhouse effect; Carbon dioxide; Atmospheric sciences; Oceanography; Ecology; Nutrient; Geology","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":[0.0002242241,0.0001612236,0.0002639825,0.0002593215,0.00008393106,0.00004484284,0.00008990993,0.0001116241,0.00003286167],"category_scores_gemma":[0.00002052405,0.0001429578,0.00003924021,0.0002060245,0.0001047818,0.0001191743,0.0000324028,0.0001980626,0.000005926536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001583284,"about_ca_system_score_gemma":0.00000692987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001694722,"about_ca_topic_score_gemma":0.002483811,"domain_scores_codex":[0.9989017,0.0001187267,0.0001879966,0.000316893,0.00008422798,0.0003904378],"domain_scores_gemma":[0.9994107,0.0003118606,0.00006014399,0.0001228769,0.000005418736,0.00008899251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001194112,0.000007175697,0.9960703,0.0001721588,0.00002229685,0.00009766955,0.0001318229,0.00002682293,0.001276858,0.0001608213,0.00001974315,0.001894981],"study_design_scores_gemma":[0.001469536,0.0003767782,0.9917625,0.0001662972,0.00004973308,0.00004649962,0.0002138405,0.004115311,0.0003371236,0.0001181209,0.0009305365,0.0004137091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968489,0.0008897422,0.00000297355,0.0002427509,0.0004862274,0.0002102171,0.00001106273,0.00003747256,0.001270609],"genre_scores_gemma":[0.9987027,0.0002116406,0.00003563706,0.0009206382,0.00009247428,0.000002005701,0.0000190826,0.000003938649,0.00001185931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004307725,"threshold_uncertainty_score":0.5829651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003050505094101783,"score_gpt":0.1645986292273206,"score_spread":0.1615481241332188,"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."}}