Streamflow input to Lake Athabasca, Canada
Bibliographic record
Abstract
Abstract. The Lake Athabasca drainage area in northern Canada encompasses ecologically rich and sensitive ecosystems, vast forests, glacier-clad mountains, and abundant oil reserves in the form of oil sands. The basin includes the Peace–Athabasca Delta, recognized internationally by UNESCO and the Ramsar Convention as a biologically rich inland delta and wetland that are now under increasing pressure from multiple stressors. In this study, streamflow variability and trends for rivers feeding Lake Athabasca are investigated over the last half century. Hydrological regimes and trends are established using a robust regime shift detection method and the Mann–Kendall (MK) test, respectively. Results show that the Athabasca River, which is the main contributor to the total lake inflow, experienced marked declines in recent decades impacting lake levels and its ecosystem. From 1960 to 2010 there was a significant reduction in lake inflow and a significant recession in the Lake Athabasca level. Our trend analysis corroborates a previous study using proxy data obtained from nearby sediment cores suggesting that the lake level may drop 2 to 3 m by 2100. The lake recession may threaten the flora and fauna of the Athabasca Lake basin and negatively impact the ecological cycle of an inland freshwater delta and wetland of global importance.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".