Experimental Simulation of Evaporation-Driven Silica Sinter Formation and Microbial Silicification in Hot Spring Systems
Bibliographic record
Abstract
Evaporation of silica-rich geothermal waters is one of the main abiotic drivers of the formation of silica sinters around hot springs. An important role in sinter structural development is also played by the indigenous microbial communities, which are fossilized and eventually encased in the silica matrix. The combination of these two factors results in a wide variety of sinter structures and fabrics. Despite this, no previous experimental fossilization studies have focused on evaporative-driven silica precipitation. We present here the results of several experiments aimed at simulating the formation of sinters through evaporation. Silica solutions at different concentrations were repeatedly allowed to evaporate in both the presence and absence of the cyanobacterium Synechococcus elongatus. Without microorganisms, consecutive silica additions led to the formation of well-laminated deposits. By contrast, when microorganisms were present, they acted as reactive surfaces for heterogeneous silica particle nucleation; depending on the initial silica concentration, the deposits were then either porous with a mixture of silicified and unmineralized cells, or they formed a denser structure with a complete entombment of the cells by a thick silica crust. The deposits obtained experimentally showed numerous similarities in terms of their fabric to those previously reported for natural hot springs, demonstrating the complex interplay between abiotic and biotic processes during silica sinter growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".