Bibliographic record
Abstract
Silica nanoparticle size distributions were measured from transmission electron micrographs of bacterial cells in thin-sectioned hot spring sediment samples, as well as specimens from laboratory experiments on bacterial silicification. Diameters of silica nanoparticles on bacterial cells were smaller than corresponding values of those occurring away from bacteria in the same fields of view. Regression analysis of the particle size data and application of the Lifshitz-van der Waals Acid-Base approach to evaluations of solid surface energy established that the size difference extends from a nearly 40% decrease in the mean interfacial energy of silica nanoparticles on bacteria (0.9 mJ/m 2 ) as opposed to free in aqueous suspension (1.2 mJ/m 2 ). In thermodynamic terms, the lower interfacial energy serves to reduce equilibrium solubility values, and enhance nucleation rates, of silica nanoparticles on bacteria cells. The well documented culmination of these events in hot spring sediments and experimental studies is rapid preferential silicification and structural preservation of bacterial cells.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".