{"id":"W2159960526","doi":"10.1093/biosci/bit001","title":"Changing Ecosystem Dynamics in the Laurentian Great Lakes: Bottom-Up and Top-Down Regulation","year":2013,"lang":"en","type":"article","venue":"BioScience","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":284,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Illinois at Urbana-Champaign; College of Engineering, Michigan State University; Michigan Department of Natural Resources; U.S. Geological Survey; Ministry of Natural Resources; University of Illinois at Chicago; National Oceanic and Atmospheric Administration; Michigan State University; U.S. Fish and Wildlife Service; University of Michigan; U.S. Environmental Protection Agency; Great Lakes Fishery Commission; China Scholarship Council; Ohio State University; New York State Department of Environmental Conservation","keywords":"Trophic level; Food web; Ecosystem; Trophic cascade; Biomass (ecology); Ecology; Lake ecosystem; Environmental science; Apex predator; Ecosystem-based management; Predation; Invertebrate; Phytoplankton; Fishery; Biology; Nutrient","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":[0.0003595191,0.00006618834,0.00005915734,0.00004665426,0.0002686926,0.00004936364,0.0002025239,0.00002865379,0.0003920613],"category_scores_gemma":[0.00002430856,0.0000452153,0.00001067727,0.0003323334,0.0001700895,0.0002978356,0.0001685453,0.00004794375,0.000137595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007430709,"about_ca_system_score_gemma":0.000001743613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001036757,"about_ca_topic_score_gemma":0.01299278,"domain_scores_codex":[0.9993085,0.00003827046,0.00008841493,0.0002110804,0.0001335231,0.0002202248],"domain_scores_gemma":[0.9997763,0.00002999618,0.00003668703,0.0001337589,0.000002865655,0.00002039516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002422236,0.00003567659,0.9710658,0.00002145704,0.000003845576,0.000003517326,0.003103536,0.00005465571,0.0003646945,0.004331368,0.01571144,0.005301651],"study_design_scores_gemma":[0.0001064754,0.00002504202,0.9766057,0.00001038937,0.000004183939,0.000003663072,0.002744631,0.0174111,0.00002661576,0.000623607,0.002347728,0.00009083262],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850081,0.00001035487,0.0002767763,0.003086439,0.0001901383,0.0003111118,0.000001650151,0.00001960901,0.01109585],"genre_scores_gemma":[0.9977919,0.0000151515,0.0001150779,0.0006031042,0.0000105294,0.00003628926,0.000001946917,0.000001984638,0.001424005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01735644,"threshold_uncertainty_score":0.7250275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006464519446927107,"score_gpt":0.192286218812458,"score_spread":0.1858216993655309,"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."}}