Chapter 3. Release of geothermal energy: hot springs and tufa–travertines
Bibliographic record
Abstract
Heat and groundwater flow through a rift basin are an integral part of its geodynamics, but predicting what is happening below the surface is often difficult due to a lack of direct information. Field observations on the occurrence, subaerial distribution, temperature and geochemistry of freshwater springs may help to form an idea of groundwater flow through the basin and what is, or has been, flowing through. Hot springs in the Albertine Rift are common and their occurrence is directly linked to deep-seated main rift-bounding faults, or major intrabasinal fault intersections. The majority of Lake Edward and Lake Albert active springs, or palaeosprings, are also associated with precipitation of localized tufa–travertine limestones. The cooler tufas may contain calcitized plant roots, leaf imprints and freshwater gastropods. Active scavenging of uranium (U) can be demonstrated in the algae and cyanobacteria that inhabit active spring mouths, and corresponding tufa–travertines are depleted in radioactive U, potassium (K) and thorium (Th) elements. The source for concentrated bicarbonate ions ( HCO 3 − ) in groundwater at depth – needed to precipitate limestones at the surface – remains problematic. However, rare earth element (REE) plus yttrium (Y) (REE + Y) geochemistry of the tufa–travertines suggest end-member sources of either carbonatites or marine limestones, indicating the possibility of a pre-Neogene rift sequence beneath the Albertine Rift.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.007 |
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".