Estimating baseline water levels for mine closure
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Baseline hydrologic data, such as groundwater levels in wells, are required to understand mine-induced impacts to the environment, both during mining operations and closure. Baseline data have natural temporal variability; however, capturing the full range of variability in baseline data is challenging. Using long-term (1900–present) climatic data, a baseline water-level record can be constructed that provides an understanding of the expected range of natural temporal variability. This paper presents an analytical approach for constructing a theoretical long-term (1900–2023) water-level record, using the Turquoise Ridge Mine Complex in northern Nevada as an example. The approach relies on an underlying conceptual model of groundwater recharge and discharge. Recharge and discharge are assumed to be in a state of dynamic equilibrium, where water levels fluctuate over annual-to-decadal timescales but have a century-scale steady-state condition. The baseline water-level record compares favourably to measured water levels, thus successfully validating the approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it