Biophysical characteristics of the stem and petiole surface of six hemlock (<i>Tsuga</i>) species and a hybrid: implications for resistance to <i>Adelges tsugae</i>
Bibliographic record
Abstract
Characteristics of the plant surface significantly affect host-plant selection by phytophagous insects. Surface morphology of six hemlock species (Tsuga spp.) and a hybrid was investigated using low-temperature scanning electron microscopy. Observations focused on trichome presence and placement and cuticle thickness. These characteristics were studied in the context of species-level host-plant resistance to the hemlock woolly adelgid, Adelges tsugae Annand (Hemiptera: Adelgidae), an exotic insect causing massive mortality to eastern hemlocks (Tsuga canadensis (L.) Carr.) and Carolina hemlock (Tsuga caroliniana Engelm.) in the eastern United States. Hemlocks in the native range of the insect do not succumb to infestations and the mechanism of resistance is unknown. We addressed the potential role of plant surface morphology in the adelgid–hemlock interaction by comparing four adelgid-resistant hemlock species and a hybrid with the two adelgid-susceptible hemlock species. We found that trichomes are likely not involved in conferring resistance to A. tsugae. Cuticle thickness may be involved in insertion site selection by A. tsugae and may therefore have implications for resistance. The cuticle is thinnest at the point of A. tsugae stylet insertion and thus may affect A. tsugae feeding.
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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".