{"id":"W2514593001","doi":"10.1111/gcb.13459","title":"Global patterns in lake ecosystem responses to warming based on the temperature dependence of metabolism","year":2016,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Physiological and biochemical adaptations","field":"Environmental Science","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Agriculture and Natural Resources; Directorate for Biological Sciences; Russian Science Foundation; Royal Society; Global Lake Ecological Observatory Network; University of Nebraska-Lincoln; National Aeronautics and Space Administration; Division of Mathematical Sciences; Ministry of Education and Science; National Science Foundation","keywords":"Global warming; Environmental science; Latitude; Climate change; Atmospheric sciences; Ecosystem; Elevation (ballistics); Climatology; Ecology; Biology; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001477955,0.0001085504,0.0001465117,0.00001011606,0.00003447751,0.000003675678,0.0003012907,0.0001026663,0.0003643143],"category_scores_gemma":[0.0001666267,0.00004804141,0.00004577217,0.0002699982,0.00007656419,0.00003067296,0.0001530242,0.00003875213,0.0001038556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009077106,"about_ca_system_score_gemma":0.000006681368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002366377,"about_ca_topic_score_gemma":0.003257837,"domain_scores_codex":[0.99907,0.0001695724,0.0001466824,0.0002725336,0.0001021689,0.000239045],"domain_scores_gemma":[0.9995676,0.0001388565,0.0000453654,0.000173461,0.000008255603,0.00006651384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003012465,0.0001312657,0.7474198,0.000005739625,0.000006370334,0.000007085663,0.00003316141,0.000007906175,0.2416017,0.001853322,0.0003722194,0.008260163],"study_design_scores_gemma":[0.0001913873,0.0001479911,0.9913708,0.00004503731,0.000003533378,0.000002141923,0.00002166944,0.00003005086,0.003615767,0.001381683,0.003076902,0.0001130225],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939876,0.00002224159,0.00006997817,0.003545635,0.00009174422,0.0002055686,0.001745439,0.00001441616,0.0003173647],"genre_scores_gemma":[0.9979525,0.000006609779,0.00008368754,0.001827437,0.00005179752,0.00005713405,0.000007105659,0.000001590308,0.00001209373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.243951,"threshold_uncertainty_score":0.3988986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03426073883872977,"score_gpt":0.2635868183642791,"score_spread":0.2293260795255493,"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."}}