Bibliographic record
Abstract
Opaline silica deposits are formed by many vascular (higher) plants. The capacity of these plants for silica absorption varies considerably according to genotype and environment. Plant communities exchange silica between soil and vegetation, especially in warmer climates. Silica deposition in epidermal cell walls offers mechanical and protective advantages. Biogenic silica particles from plants are also implicated in the causation of cancer. Recent techniques are reviewed which may aid in the identification of plant pathways for soluble silica movement to deposition sites and in the determination of ionic environments. Botanical investigations have focused on silicification of cell walls in relation to plant development, using scanning and transmission electron microscopy combined with X-ray microanalysis. Silica deposition in macrohair walls of the lemma of canary grass (Phalaris) begins at inflorescence emergence and closely follows wall thickening. The structure of the deposited silica may be determined by specific organic polymers present at successive stages of wall development. Lowering of transpiration by enclosure of Phalaris inflorescences in plastic bags reduced silica deposition in macrohairs. Preliminary freeze-substitution studies have located silicon, as well as potassium and chloride, in the cell vacuole and wall deposition sites during initial silicification.
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 | 0.001 |
| 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) | 0.002 | 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".