{"id":"W2553042268","doi":"10.1016/j.jglr.2016.10.007","title":"Lake whitefish ( Coregonus clupeaformis ) energy and nutrient partitioning in lakes Michigan, Erie and Superior","year":2016,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Fisheries and Oceans Canada; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Great Lakes Fishery Trust","keywords":"Coregonus clupeaformis; δ15N; Biology; Food web; Predation; Reproduction; Ecology; Fishery; Trophic level; δ13C; Stable isotope ratio","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001482791,0.0001390985,0.0001754854,0.0005434779,0.0007602601,0.0005434342,0.000197911,0.0002922077,0.001069305],"category_scores_gemma":[0.0003209463,0.0002374362,0.0001532972,0.0004027946,0.0003581386,0.0004204973,0.0006062863,0.0001398893,0.0001318793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001385706,"about_ca_system_score_gemma":0.0005526203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1216268,"about_ca_topic_score_gemma":0.4573661,"domain_scores_codex":[0.9999175,0.000009376737,0.000007329898,0.00002487017,0.0000172714,0.00002370839],"domain_scores_gemma":[0.9998187,0.00002167739,0.00005818413,0.000005711163,0.00004586085,0.00004979021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004626315,0.00004509263,0.9787304,0.00002289987,0.0000851747,0.0001118622,0.001260636,0.0001933645,0.01643321,0.00009856354,0.0001903725,0.00236576],"study_design_scores_gemma":[0.000002501661,0.00001986873,0.9991366,0.000001458734,0.000008672155,0.00002076544,0.0003477847,0.000129359,0.0002252755,0.000009077805,0.00009738372,0.000001244168],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997597,0.00001502569,0.00001218275,0.00000697384,3.262238e-7,7.334513e-7,0.00004113089,7.18537e-7,0.0001631958],"genre_scores_gemma":[0.9994102,0.00001403925,0.00003589681,0.000009116804,5.970396e-7,0.000003086021,0.00008188771,9.562162e-7,0.0004442908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1216268,"threshold_uncertainty_score":0.2418376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0243551928272077,"score_gpt":0.2747292855616729,"score_spread":0.2503740927344652,"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."}}