Siliceous shrubs in hot springs from Yellowstone National Park, Wyoming, U.S.A.
Bibliographic record
Abstract
Many of the siliceous hot springs in Yellowstone National Park contain subaqueous, spinose siliceous precipitates up to 5 cm high that occupy shallow terracettes in siliceous terraced mound accumulations, discharge channels, etc. These siliceous "shrubs" are composed of opal-A with an arborescent or branching pattern and have strong morphological similarities to bacterial shrubs from carbonate-precipitating hot springs. Siliceous shrubs constitute a major precipitate style associated with discharge channel flow-path facies throughout most of the 20 m of flow path at Cistern Spring, Norris Geyser Basin. They are found in siliceous spring waters ranging in temperature from 76.4 to 16.2 °C and pH from 6.0 to 7.4. At every scale, siliceous shrubs contain abundant evidence of microbial life in the form of bacterial body fossils and extracellular polymeric substances. The presence of relict organic constituents and bacterial morphological fossils indicates that the shrub fabric and architecture are dominated by bacteria, i.e., there is potentially a strong biotic effect on the precipitation process. Precipitation of opal in siliceous shrubs is very likely the result of either active bacterially induced precipitation or passive mediation through organic templates. On a larger scale, siliceous shrubs contain abundant evidence of former microbial activity in hot springs, thus they are good microbial biomarkers.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".