Ex situ germination as a method for seed viability assessment in a peatland orchid, <i>Platanthera blephariglottis</i>
Bibliographic record
Abstract
UNLABELLED: • PREMISE OF THE STUDY: Assessing seed quality in orchids has been hindered by stringent germination requirements. Seed quality has traditionally been assessed in orchids using in vitro or in situ germination protocols or viability staining. However, these methods are not always well suited for rapid assessment of viability in the context of ecological studies.• METHODS: The potential of an ex situ protocol for seed viability assessment of orchids in ecological studies was investigated by sowing seeds of Platanthera blephariglottis on Sphagnum moss collected in the orchid's natural habitat. Ex situ germination results were compared with those obtained by viability staining using triphenyltetrazolium chloride (TTC), and the effect of seed testa color on staining and germination results was investigated.• KEY RESULTS: The ex situ protocol yielded high germination rates, with 66% of the seeds germinating after 9 wk. Depending on the seed testa color class, ex situ germination rates were about 1.4 to 2.5 times higher than viability rates determined using TTC, indicating that the TTC technique underestimated viability compared with the method using ex situ germination. The TTC estimates of viability rates were higher for seeds with dark-colored testae than for pale ones, whereas seed testa color had no effect on germination.• CONCLUSIONS: Our study showed promising results for the use of ex situ germination as an alternative to previously developed protocols for seed viability assessment of orchids in ecological studies. Staining using TTC might not be well suited for this purpose, since it introduced a bias with respect to seed testa color.
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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".