Imprints of large‐scale climate oscillations on river flow in selected Canadian river catchments
Bibliographic record
Abstract
Abstract We investigated the impacts of six major climate oscillations on river flow at three stations within the Humber catchments (located in Ontario, ON and Newfoundland and Labrador, NL) from 1970 to 2020 using sensitivity and wavelet analyses. Results indicate that the discharge at East Humber River near Pine (ON) exhibits the highest statistically significant sensitivity, with 0.304 and 0.394 monthly units to the Dipole Mode Index (DMI) and Tropical North Atlantic (TNA), respectively. Monthly significance analysis also highlights the diverse influence of large‐scale climate oscillations on river flow across the three locations. Wavelet analysis reveals significant active multidecadal oscillations for the North Atlantic Oscillation (NAO) at East Humber River near Pine, with high spectral power. We confirmed that stations within ON demonstrate sensitivities in a similar direction to the large‐scale climate oscillations, contrasting with those observed at NL. The observed inconsistency in the relationship between large‐scale climate oscillations and, for instance, NAO at various locations suggests that the impacts of climate oscillations may manifest differently in different regions. Overall, while inland stations exhibit similar sensitivity patterns, the coastal station demonstrates distinct responses, highlighting the importance of geographical context in understanding the impacts of large‐scale climate oscillations on river flow dynamics.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".