Bibliographic record
Abstract
Abstract A wide variety of ancient and modern hot spring systems are characterized by authigenic silica precipitation and sinter formation. In these systems, the chemical disequilibrium of venting hydrothermal fluids leads to the nucleation and growth of amorphous silica masses and simultaneously the mineralization, and potential fossilization, of many different types of microorganisms. Source waters originating from deep, hot reservoirs, at equilibrium with quartz, commonly contain dissolved silica concentrations significantly higher than the solubility of amorphous silica at 100°C (approximately 400 ppm; Figure 1) (Gunnarsson and Arnórsson, 2000). Upon the discharge of these fluids at the surface, decompressional degassing and boiling, rapid cooling to ambient temperatures, evaporation, and changes in solution pH all work together to cause the solution to rapidly exceed amorphous silica solubility (Fournier, 1985). Under these conditions, silicic acid dissolved in the monomer form Si(OH)4 spontaneously polymerizes initially to oligomers (e.g., dimmers, trimers and tetramers), and then to polymeric species with spherical diameters of 1-5 nm, as the silanol groups (-Si-OH-) of each oligomer condense and dehydrate to produce the siloxane (-Si-O-Si-) cores of larger polymers. The polymers quickly grow in size such that a bimodal composition of monomers and particles of colloidal dimensions (>5 nm) are generated (Crerar et al., 1981). Depending on the degree of supersaturation, these either remain in suspension, due to the external silanol groups exhibiting a residual negative surface charge due to a low zero point of charge (around pH 2), they coagulate via cation
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".