Attribution of hydrological trends and change points in the discharge of Mackenzie River during 1972-202
Bibliographic record
Abstract
Due to the amplification of climate change in the polar regions, the changes in discharge are more pronounced for the Arctic rivers, which are relevant to other hydro-climatic indicators (e.g., precipitation, snowmelt, groundwater, and permafrost) in the river basin. To investigate the recent changes of river discharge in the Mackenzie River Basin (MRB) responding to climate change, this study used the Mann-Kendall trend test and correlation coefficient approach to examine the long-term variability in discharge at three gauges along the watercourses of MRB between 1972 and 2020, focusing on the inter-decadal trends and the occurrence of hydrological extremes. From the 1970s to 2000s, the discharge in the MRB has increased significantly. However, a reverse trend was shown in the 2010s that is more pronounced in winter and spring. Moreover, the analyses in annual discharge have revealed that the extremely low discharge in 1994/1995 is highly associated with the changes in snowfall, while the extremely high discharge events in 2012/13 and 2019/2020 are more influenced by the reduced sea ice extent and peatland burning over the last decades.
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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 | 0.001 |
| 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) | 0.001 | 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".