The Characterization Of CaCO<sub>3</sub> in a Geothermal Environment: A Sem/Tem-Eels Study
Bibliographic record
Abstract
Abstract Mineralization of microbial biomass is a common phenomenon in geothermal habitats, but knowledge of the structure of the minerals formed in these environments is limited. A combination of spectroscopic, microscopic, and stable isotopic methods, as well as the chemical analysis of spring water, were employed in the present study to characterize calcium carbonate minerals deposited in filamentous cyanobacterial mats in different locations of La Duke hot spring, a circumneutral thermal feature near the north entrance of Yellowstone National Park, Montana, USA. Calcite was the primary crystalline mineral phase associated with biofilm-containing deposits closest to the source of the spring and the suspended microbial biomass in a pool further from the source. The carbonate minerals at all sites occurred as aggregated granules, ~2 μm in diameter, in close association with the microbial biomass. Only in the deposits closest to the source were the granules organized as laminated structures interspersed with microbial biomass. The calcium carbonate grains contained two distinct regions: a dense monolithic calcite core and a porous dendritic periphery containing organic matter (OM). Electron energy loss spectroscopy (EELS) indicated that the voids were infilled with OM and carbonates. The EELS technique was employed to distinguish the source of carbon in the organic matter and carbonate mixture. The studies of carbon isotope compositions of the calcium carbonates and the saturation indices for calcite in the spring waters suggest that processes (abiotic vs. biotic) controlling the carbonate formation may vary among the sampling sites.
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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) | 0.000 | 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".