Revisiting Mt Fuji’s groundwater origins with helium, vanadium and environmental DNA tracers
Bibliographic record
Abstract
Known locally as the water mountain, for millennia Japan's iconic Mt Fuji has provided safe drinking water to millions of people via a vast network of groundwater and freshwater springs. Groundwater, which is recharged at high elevations, flows down Fuji's flanks within three basaltic aquifers, ultimately forming countless pristine freshwater springs among Fuji's foothills. Here we challenge the current conceptual model of Fuji being a simple system of laminar groundwater flow with little to no vertical exchange between its three aquifers. This model contrasts strongly with Fuji's extreme tectonic instability due to its unique location on top of the only known continental trench-trench-trench triple junction, its complex geology and its unusual microbial spring water communities. On the basis of a unique combination of microbial environmental DNA, vanadium and helium tracers, we provide evidence for prevailing deep circulation and a previously unknown deep groundwater contribution to Fuji's freshwater springs. The most substantial deep groundwater upwelling has been found along Japan's most tectonically active region, the Fujikawa-kako Fault Zone. Our findings broaden the hydrogeological understanding of Fuji and demonstrate the vast potential of combining environmental DNA, on-site noble gas and trace element analyses for groundwater science.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".