Bibliographic record
Abstract
Abstract Ice jamming during the spring breakup of the ice cover in the lower reaches of the Peace River has been identified as the main agent of flooding and replenishment of the Peace–Athabasca delta (PAD) ecosystems. The relative rarity of major ice jams in the lower Peace River following construction of the Bennett Dam has resulted in serious habitat degradation and risk to local ecology, and concern has been raised over potential climate change impacts. This issue is under active study that encompasses use of various types of model, field data collection, and analysis of archived records. An important component of the study aims at determination of threshold flows that can result in significant flooding when a jam is in place in the PAD reach of the Peace. This question is investigated by means of RIVJAM, a numerical model that computes the water surface and thickness profiles of a jam in a given river reach. First, the model is calibrated using field data obtained during the 1996 and 1997 ice‐jam floods. Calibration coefficients are shown to be the same for both events and consistent with default values determined from previous applications in other rivers. A by‐product of the calibration process is the quantification of the flow reversals occurring under high‐stage conditions in the three major tributaries of the lower Peace. Next, the model is applied with increasing flow values and the resulting water surface profiles are compared with bank elevations. These comparisons indicate that an incoming flow of at least 4000 m3 s−1 is required to produce significant flooding of the delta. The calibrated model can also be used to examine the efficacy of controlled water releases at the Bennett Dam as a means of enhancing flooding potential. Copyright © 2003 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".