3D X-ray microscopy lights up nanoparticles in plants
Bibliographic record
Abstract
Abstract The discovery of novel plant fertilization strategies heavily relies on our capabilities to probe physiological processes in living plants with sub-cellular precision. State-of-the-art microscopy techniques are in general limited to surface investigation or they require elaborated tissue preparation and often destruction. X-ray microscopy has the potential to resolve some of these limitations by generating micro-to nanometer-scale 3D images deep into the tissue. We introduce experimental designs and the quantitative analysis methodologies, pioneering nanoscale (≈150 nm resolution) in-vivo 3D microscopy of plant tissue. We show the first direct in-vivo visualization of foliar-applied untagged nanoparticulate fertilizers deep under the leaf surface, not accessible by other microscopy methods. Ultimately, our approach provides the means for a direct observation of nanoparticle transport and dissolution in living plant tissue, a step critical for developing sustainable plant fertilization approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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 teacher head, 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".