In situ three-dimensional visualization of <i>Bursaphelenchus xylophilus</i> inoculated in <i>Pinus thunbergii</i> using X-ray micro-computed tomography
Bibliographic record
Abstract
Pine wilt disease, a devastating infectious disease of pine trees, is caused by the pinewood nematode, Bursaphelenchus xylophilus. It is important to understand the spatial dispersal processes of B. xylophilus within host-tree tissues to assess its pathogenic mechanism. However, this is not feasible with conventional microscopy-imaging techniques. In this study, we showed that X-ray micro-computed tomography (micro-CT) imaging can be a powerful tool for visualizing infected nematodes within host-tree tissues. We visualized 161 nematodes and 11 eggs within a Pinus thunbergii stem section, 47.3 mm3 in volume, using an appropriate segmentation of the micro-CT images. Quantitative measurements of the segmented region corresponding to the nematodes allowed for the calculation of the longitudinal length and a-value, which were similar to previous morphological descriptions of B. xylophilus. The technique adopted in this study can aid in understanding the behavior of and obtaining quantitative information on B. xylophilus within tree tissues.
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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 | 0.001 |
| 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".