New ecosystems in the deep subsurface follow the flow of water driven by geological activity
Bibliographic record
Abstract
Eukarya have been discovered in the deep subsurface at several locations in South Africa, but how organisms reach the subsurface remains unknown. We studied river-subsurface fissure water systems and identified Eukarya from a river that are genetically identical for 18S rDNA. To further confirm that these are identical species one metazoan species recovered from the overlying river interbred successfully with specimen recovered from an underlying mine at -1.4 km. In situ seismic simulation experiments were carried out and show seismic activity to be a major force increasing the hydraulic conductivity in faults allowing organisms to create ecosystems in the deep subsurface. As seismic activity is a non-selective force we recovered specimen of algae and Insecta that defy any obvious other explanation at a depth of -3.4 km. Our results show there is a steady flow of surface organisms to the deep subsurface where some survive and adapt and others perish. As seismic activity is also present on other planets and moons in our solar system the mechanism elucidated here may be relevant for future search and selection of landing sites in planetary exploration.
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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) | 0.000 | 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 | 0.001 |
| 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".