Genecology and seed zones for tapertip onion in the US Great Basin
Bibliographic record
Abstract
The choice of germplasm is critical for sustainable restoration, yet seed transfer guidelines are lacking for all but a few herbaceous species. Seed transfer zones based on genetic variability and climate were developed using tapertip onion (Allium acuminatum Hook.) collected in the Great Basin and surrounding areas in the United States. Bulbs from 53 locations were established at two common garden sites and morphological (such as leaf and scape dimensions), phenological (such as bolting date and flowering), and production traits (such as emergence and seeds per plant) were measured. Differences among source locations for plant traits within both common gardens were strong (P < 0.001), indicating genetic variation. Principal component 1 (PC 1) for phenological traits, with R2 = 0.59, and PC 1 for production traits, with R2 = 0.65, were consistently correlated with annual, maximum, minimum, and average temperature, annual precipitation, and frost-free days at source locations (P < 0.05). Regression of PC 1 phenology and PC 1 production scores with source location climates resulted in models with R2 values of 0.73 and 0.52, respectively. Using a geographic information system, maps of these models were overlaid to develop proposed seed zones to guide the choice of germplasm for conservation and restoration of tapertip onion across the collection region.
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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 | 0.001 | 0.001 |
| 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".