HISTORICAL AND ESTIMATED GROUND WATER LEVELS NEAR WINNIPEG, CANADA, AND THEIR SENSITIVITY TO CLIMATIC VARIABILITY<sup>1</sup>
Bibliographic record
Abstract
ABSTRACT: Long term well hydrographs and estimated ground water levels derived from hydroclimatic and biological data were used to evaluate trends within the Upper Carbonate Aquifer (UCA) near Winnipeg, Canada, during the 20th Century. Ground water records from instruments have been kept since the early 1960s and are derived from piezometers in the overlying sediments and in open boreholes in the UCA. Some boreholes extend into an underlying Paleozoic carbonate sequence. Shallow well hydrographs show no obvious long term trends but do exhibit variations on the order of three to four years that are correlated with changes in annual temperature and precipitation at lags up to 24 months. Trends observed in deeper wells appear to be largely related to ground water usage patterns and show little correlation with climate over the past 35 years. Stepwise multiple regression modeled average annual hydraulic head in the shallow wells as a function of regional temperature, precipitation, and tree ring variables. Estimated hydraulic heads had a slightly greater range prior to the 1960s, most prominently during an interval of lowered ground water levels between 1930 and 1942. Regression results demonstrate that moisture sensitive tree ring data are viable predictors of past ground water levels and may be useful for studies of aquifers in regions that lack long, high quality precipitation records.
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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 | 0.001 | 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) | 0.001 | 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".