Analysis of air/river maximum daily temperature characteristics using the peaks over threshold approach
Bibliographic record
Abstract
Abstract The understanding of river temperature is very important when assessing fish habitat conditions in terms of fish growth as well as fish distribution within river systems. The quantification of extreme water temperatures is also important, especially when studying the suitability of thermal habitats during high air/water temperature events. The present study deals with the analysis of extreme air and water temperatures using the partial duration series approach, also known as the peak over threshold (POT) approach. The advantage of the POT approach is that extreme air and water temperatures can be described not only in magnitude but also in duration and degree day accumulation for each event. In the present study, 74 years of air temperature data (Miramichi meteorological station) were analysed as well as 21 years of river temperature data from the Little Southwest Miramichi River. For example, results showed that the 0.01 exceedance probability ( F ( x ) = .99) for maximum daily air temperature event was calculated at 38.4°C whereas for the same exceedance probability, the maximum daily water temperature event was slightly lower at 32.7°C. The duration of events varied between 1 and 5 days for air temperature and between 1 and 7 days for water temperature. Maximum daily water temperature exceeding 30°C generally occurred over a period of 3 days or more, and the degree day accumulation was higher than 6°C·day. This study showed that the POT approach was effective in quantifying both air and water temperature extremes within the Miramichi River study area.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".