Effects of cold stratification on the germination of<i>Vaccinium myrtilloides</i>(common blueberry) and<i>Vaccinium vitis-idaea</i>(bog cranberry) seeds from Alberta, Canada
Bibliographic record
Abstract
Vaccinium vitis-idaea L. (Ericaceae) and Vaccinium myrtilloides Michx. are important agronomic and ecological species. Several food products are derived from these species throughout Europe and North America, and they are becoming important plants for land reclamation. Several studies have indicated that stratification can be beneficial for the germination of Vaccinium seed species including V. vitis-idaea and V. myrtilloides; however, the recommended stratification lengths vary from 12 wk to 10 mo. This study investigated the optimal time for cold stratification of V. vitis-idaea and V. myrtilloides seeds collected in Alberta, Canada. Seed treatments consisted of unstratified as well as 2, 4, and 8-wk stratification periods. Our results indicate that the 8-wk cold stratification period provided the highest mean germination and uniformity for V. vitis-idaea, but mean germination time was longer compared to the other stratification treatments. Moreover, 8-wk stratified V. myrtilloides seeds showed the lowest average germination percentage and the least amount of synchronization. Similar studies involving V. vitis-idaea presented comparable findings to this study but further studies are required to determine stratification strategies for V. myrtilloides. Further research of V. myrtilloides seed characteristics, such as dormancy, may be beneficial for gaining a better understanding of the effects of stratification on germination.
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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 | 0.001 | 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".