Effect of Water and Methanol Extracts of Common Buckthorn Berries on the Germination and Growth of Lettuce and Native Grass Seeds
Bibliographic record
Abstract
The Common Buckthorn (Rhamnus cathartica) is an invasive species and a major threat to natural areas in Minnesota. The purpose of this research was to determine if water and methanol extracts of berries of the Common Buckthorn will reduce the germination and growth of lettuce and native grass seeds (Little Blue Steam, Bottlebrush and/or Canada Wild Rye). The berries were collected last fall and refrigerated. The berries were macerated in a blender. Different amounts of the berries were extracted with water by agitating for 5 minutes with a Vortex mixer and then centrifuged for 10 minutes at 2500 rpm. Water extracts (10 mls) were added to Petri dishes lined with filter paper and containing 10 seeds. Then methanol was added to the berries and the processes repeated. All methanol extracts were allowed to evaporate before adding 10 seeds and 10 mls of distilled water. All treatments were done in triplicate. Water and methanol controls were also done in triplicate. The seeds were incubated at 25C under 14 hour light/10 hour dark cycle. Germination of seeds was monitored daily and at the end of incubation period the root length of each seed that germinated was measured. The results of this research will be presented.
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 | 0.000 | 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".