3Department of Fisheries and Oceans, Resource and Environmental Sciences
Bibliographic record
Abstract
ABSTRACT In order to provide better estimates of the thermal-induced stress encountered by salmon migrating to their spawning grounds, a model is used to hindcast temperatures throughout the mainstem Fraser and Thompson Rivers back to 1953. Tributary and headwater temperatures that are not available prior to 1993 are estimated with both linear regression and neural network techniques. The average root mean square difference between model temperatures and those observed at Hell’s Gate, on the lower Fraser River, is computed to be 1.12°C. Historical flow and temperature observations are also used to establish patterns and trends for the Fraser River watershed. The Julian day numbers by which one-third and one-half of the integrated yearly discharge had occurred were computed and found to be progressing earlier at the rates of 0.11 and 0.09 days per year, respec-tively. Both values are significant at the 95 % level. Average summer Hell’s Gate temperatures from 1941 to 1998 are warming at the rate of 0.012°C per year, though the relatively large standard error of 0.008°C means that this result is not significantly different from zero at the 95 % level. However, when the analysis is restricted to 1953 to 1998, the trend becomes 0.022°C per year and the significance level rises to 98%. An analysis of the 1953–98 atmosphere-to-river heat exchange at Kamloops and Prince George produces positive increases of 0.52 W m–2 per year and 0.90 W m–2 per year, respectively. When these trends are used to force the river temperature
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.374 | 0.132 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".