Ultrastructure of the alveolar network and its relation to coating on vessel walls in elms infected by Ophiostoma novo-ulmi and in other plants affected with similar wilt diseases
Bibliographic record
Abstract
In elms infected with Dutch elm disease, alveolar networks, demarcated by filamentous-like bands and confluent with similar matter (the coating) accumulating on vessel walls, occurred regularly in vessel elements. Similar material lined vessel walls in inoculated, sterilized, thin elm wood sections fixed by high pressure freezing. The coating was observed to connect with fungal cells and occasionally contained small opaque particles, the size of ribosomes, membranous and vesicular structures, and, following incubation of wood chips taken from diseased samples incubated on an agar medium, it still displayed similar matter. Coating and alveolar bands increased in thickness by confluence of other bands or membranous structures. Similar matter and structures also occurred in other plants affected by similar fungal wilt diseases. In all systems, the compact coating did not label for chitin, cellulose and pectin. In staghorn sumac, the probe for DNA attached to the coating. Altogether, in the light of these data, it appears that the coating and alveolar networks are not inert components, a fact which indicates their primordial probable pathogen origin. It is proposed that these elements might be important not only in the initial infection stages but also in older or recurrent infections at a time when host resistance mechanisms are ineffective.
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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) | 0.000 | 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 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".