Non-destructive diffraction enhanced imaging of seeds
Bibliographic record
Abstract
Techniques that make possible the non-destructive continuous observation of plant anatomy and developmental processes provide novel insights into these phenomena. Non-destructive imaging of seeds was demonstrated using the synchrotron-based X-ray imaging technique, diffraction enhanced imaging (DEI). The seed images obtained had good contrast and definition, allowing anatomical structures and physiological events to be observed. Structures such as hypocotyl-root axes, cotyledons, seed coats, air cavities, and embryo-less Brassica napus L. seeds were readily observed using DEI. Embryo axes, scutella, pericarp furrows, coleoptiles, and roots were observable over a time-course in individual germinating Triticum aestivum L. caryopses. Novel anatomical and physiological observations were also made that would have been difficult to make continuously using other techniques. The physical principles behind DEI make it a unique imaging technique. Contrast in DEI is the result of X-ray refraction at the density differences occurring at tissue boundaries, scatter caused by regions containing ordered molecules such as cellulose fibres, and attenuation. Sectioning of samples and the infusion of stains or other contrast agents are not necessary. Furthermore, as high-energy X-rays are used (30-40 keV), little X-ray absorption occurs, resulting in low levels of radiation damage. Consequently, studies of developmental processes may be performed on individuals. Individual germinating B. napus and T. aestivum seeds were imaged at several time points without incurring any apparent radiation damage. DEI offers a unique way of examining plant anatomy, development, and physiology, and provides images that are complementary to those obtained through other techniques.
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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".