Precision thin sectioning of silica phytoliths by Focused Ion Beam (FIB-SEM) v1
Bibliographic record
Abstract
Phytoliths are microbodies of biogenic silica made by many plant species in all ecosystems over the globe. They serve critical functions in alleviating plant stresses and influencing the carbon and silicon biogeochemical cycles. The investigation of carbon occlusion within phytolith, as a potential source of long-term soil carbon storage, has long been hampered by a lack of direct experimental evidence. In this protocol, we employed a Focused Ion Beam coupled to a Scanning Electron Microscopy (FIB-SEM) to produce thin lamellas (approximately 15 × 10 µm2 size, with thickness below 200 nm) enabling synchrotron scanning transmission X-ray microspectroscopy (STXM) analysis with ≈100–200 nm pixel size resolution at energies near the silicon and carbon K-absorption edges. Our results revealed the spatial distributions of carbon within phytoliths, highlighting its presence at lamella borders, within islands, and dispersed in extended regions. This protocol of phytolith slicing into thin lamella provides unprecedented insights into the spatial and chemical characteristics of carbon within phytoliths, offering a low-invasive alternative to wet-chemical digestion methods.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".