Spatial and temporal trends of muscle lipid content in Great Lakes fishes: 1970s–2008
Bibliographic record
Abstract
An evaluation of spatial and temporal trends in fish lipid content may provide insight into trends of lipophilic contaminant levels, fish population health, and nutritional benefits to fish consumers. Currently, little is known about lipid content in fishes of the Great Lakes, where commercial and recreational fisheries are important. We examined 35+ years of muscle lipid content data for ten Great Lakes fishes from Canadian waters and found lipid content to have significantly (p < 0.05) declined in 2/6 species in Lake Superior, 3/8 species in Lake Huron, 1/8 species in Lake Erie, and 5/10 species in Lake Ontario. Lake Erie showed the least number of declining trends and most increasing trends (2/8 populations, p < 0.1). For most species, recent (2000–2008) muscle lipid values for Lakes Erie and Ontario are significantly higher compared with Lakes Superior and Huron. These observed trends may be linked to a number of environmental changes within the Great Lakes, and the mechanism(s) of decline are likely to be complex.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".