Silver nitrate (AgNO<sub>3</sub>) as an alternative contrast agent for X-ray imaging of wheat tissue samples
Bibliographic record
Abstract
One of the challenges in using X-ray computed tomography (CT) for plant imaging is lack of contrast in anatomical structures and tissues due to similar density. Iodine is the most commonly used contrast agent and studies on additional contrast agents are scarce. In the present study, we describe the successful application of silver nitrate (AgNO3) as a novel contrast agent in synchrotron-based CT of wheat. The lower K-edge of silver (25.514 keV) is more optimal for plant imaging than a high atomic number contrast agent, such as iodine (33.164 keV), for which the below- and above-edge images would have poorer absorption contrast (due to reduced ratio of absorption coefficients from plants). Particularly, this is applicable for studies at the Biomedical Imaging and Therapy beamline (BMIT-BM) at the Canadian Light Source due to the peak flux of the beamline being proximal to the K-edge of silver in comparison to iodine (leading to decreased image noise, increased contrast, and a better signal-to-noise ratio).
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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 | 0.001 | 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".