The Microbial Role in Hot Spring Silicification
Bibliographic record
Abstract
Recent experimental studies indicate that microorganisms play a passive role in silicification. The organic functional groups that comprise the outer cell surfaces simply serve as heterogeneous nucleation sites for the adsorption of polymeric and/or colloidal silica, and because different microorganisms have different cell ultrastructural chemistry, species-specific patterns of silicification arise. Despite their templating role, they do not appear to increase the kinetics of silicification, and at the very most, they contribute only marginally to the magnitude of silicification. Instead, silicification is due to the polymerization of silica-supersaturated hydrothermal fluids upon discharge at the surface of the hot spring. Microorganisms do, however, impart an influence on the fabric of the siliceous sinters that form around hot spring vents. Different microorganisms have different growth patterns, that in turn, affect the style of laminations, the primary porosity of the sinter and the distribution of later-stage diagenetic cementation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".