The Formation and Preservation of<i>Synechococcus elongatus</i>Cell Molds in Simulated Silica Sinter: Implications for the Identification of Microfossils
Bibliographic record
Abstract
Siliceous sinters that precipitate around modern hot spring systems are able to fossilize the indigenous microbial communities, forming molds that accurately outline the shape of the microorganisms. Over time, the biomass decays, and only silica molds or their infill may remain as evidence of the former living cells. However, little is known regarding the fidelity of such silica molds in terms of size and morphology, and the preservation of critical parameters for the identification of ancient silicified microorganisms by silica molds remains untested. Here we report experiments examining the formation of microbial molds of the cyanobacterium Synechococcus elongatus in silica gel. We demonstrate that post-depositional processes, primarily desiccation, are crucial for obtaining accurate and robust molds, and that initial desiccation acts to strengthen cell molds against further alteration. However, all silica gel treatments systematically created preservational biases (changes in size, additional structures) that may be misleading and may complicate the identification of fossil microorganisms.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".