The Influence of Air Temperature on Water Temperature and the Concentration of Dissolved Oxygen in Newfoundland Rivers
Bibliographic record
Abstract
In this paper regression models are developed for predicting water temperature and the concentration of dissolved oxygen in rivers monitored by the Newfoundland and Labrador Real-Time Water Quality Monitoring (RTWQM) network. The developed models can be used to predict mean, maximum and minimum water temperatures and dissolved oxygen at the monthly, weekly and daily time scales. A nonlinear logistic model is found to best represent the S-shaped relationship between water temperature at the real-time stations and air temperature collected from meteorological stations 5-50 kilometers away. There is a clear tendency for monthly and weekly models to be more accurate for prediction than the daily models. Both linear and nonlinear exponential decay models were found to best represent the relationship between water temperature and dissolved oxygen at the real-time stations. A novel graphical method of linking air temperature to water temperature and dissolved oxygen has been developed and may prove to be a valuable simple tool in the assessment of the health of the rivers in the real-time network.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".