Comparison of lake whitefish (Coregonus clupeaformis ) growth in Lake Erie and Lake Ontario.
Bibliographic record
Abstract
Growth is the ultimate response of an organism to its environment. The objective of this study was to compare growth of lake whitefish ( Coregonus clupeaformis) in Lake Erie and Lake Ontario, from 1954 to 2003. Trends in lake whitefish abundance were similar in Lake Erie and Lake Ontario from the 1950s until 1990, when abundance began to decline in Lake Ontario while remaining relatively stable in Lake Erie. Although both lakes have undergone similar environmental changes, from decreasing phosphorous loading to invasion by dreissenid mussels, declining growth and condition were more pronounced in Lake Ontario. Trends in abundance, growth, and condition of lake whitefish from Lake Erie and Lake Ontario were compared for the period 1990 to 2003. In 2003, lake whitefish were collected from both lakes to describe seasonal diet, energy density, and female GSI. Growth, described as length-at-age, declined significantly in Lake Ontario but did not change in Lake Erie. Lake whitefish energy density (J/g wet mass) was significantly higher in Lake Erie than in Lake Ontario. Biological attributes of lake whitefish from Lake Erie did not change greatly from 1990 to 2003 while fish from Lake Ontario exhibited signs of stress, including decreased size-at-age and condition. (Abstract shortened by UMI.) Source: Masters Abstracts International, Volume: 44-03, page: 1280. Thesis (M.Sc.)--University of Windsor (Canada), 2005.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".