Phenotypic diversity in four woody species on the Canadian prairies
Bibliographic record
Abstract
Genetic diversity is a prerequisite for plant adaptation and maintenance of a sustainable ecosystem. Not much information is available on the genetic diversity of woody species on the semi-arid Canadian prairies. We used RAPD fragments to assess the diversity of four woody species of the Elaeagnaceae family, sea buckthorn (Hippophae rhamnoides L.), Russian olive (Elaeagnus angustifolia L.), buffaloberry (Shepherdia argentea Nutt.) and silverberry (Elaeagnus commutata Bernh. Ex Rydb.) collected from several locations in southwestern Saskatchewan. The RAPD fragments were used to generate molecular data for this experiment. Of the total scorable RAPD fragments, 86, 80, 55.2, and 36.5% were polymorphic in sea buckthorn, buffaloberry, silverberry and Russian olive, respectively. Estimates of phenotypic diversity by AMOVA and Shanon's information index revealed that buffaloberry and sea buckthorn had relatively high phenotypic diversity and Russian olive had low phenotypic diversity. Key words: Sea buckthorn, silverberry, buffaloberry, Russian olive, RAPD, phenotypic diversity, Hippophae, Elaeagnus, Shepherdia
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| 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".