Ambiguous Hydraulic Heads and <sup>14</sup> C Activities in Transient Regional Flow
Bibliographic record
Abstract
A regional flow and transport model is used to explore the implications of significant variability in Pleistocene and Holocene climates on hydraulic heads and (14)C activity. Simulations involve a 39 km slice of the Death Valley Flow System through Yucca Mountain toward the Amargosa Desert. The long-time scale over which infiltration has changed (tens-of-thousands of years) is matched by the large physical extent of the flow system (many tens-of-kilometers). Estimated paleo-infiltration rates were estimated using a juniper pollen percentage that extends from the last interglacial (LIG) period (approximately 120 kyrbp) to present. Flow and (14)C transport simulations show that groundwater flow changes markedly as a function of paleoclimate. At the last glacial maximum (LGM, 21 kyrbp), the recharge to the flow system was about an order-of-magnitude higher than present, and water table was more than 100 m higher. With large basin time constants, flow is complicated because hydraulic heads at a given location reflect conditions of the past, but at another location the flow may reflect present conditions. This complexity is also manifested by processes that depend on flow, for example (14)C transport. Without a model that accounts for the historical transients in recharge for at least the last 20,000 years, there is no simple way to deconvolve the (14)C dates to explain patterns of flow.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".