A hydrometric analysis of the Moose Jaw River near Burdick (05JE006): Temporal trends and frequency analyses for mean, minimum, and maximum flows
Bibliographic record
Abstract
Abstract A hydrometric analysis over the available historical record (1973-2010) was conducted for the Moose Jaw River station near Burdick in south-central Saskatchewan, Canada. Frequency analyses on mean monthly, average annual, monthly minimum/maximum, and annual minimum flows generally yielded poor fits, and problems with negative flow predictions for mid- to long-term return periods regardless of distribution type. The annual maximum streamflow time series is reasonably well-described by linear and log Pearson Type III distributions, although both distribution types underestimate extreme maximum flows. Mann-Kendall linear time series analysis on mean monthly and annual streamflows reveals no trend in annual water yields, nor in mean monthly flows between March and October. There is ambiguity as to whether statistically significant negative time trends in overwinter period mean monthly flows and monthly minimum/maximum flows for the hydrometric station are real or whether they represent a change in measurement technique/calibration during the mid-/late-1980s.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".