The effect of temperature and water potential on seed germination of poly-cross side-oats grama (Bouteloua curtipendula (Michx.) Torr.) population of Canadian prairie
Bibliographic record
Abstract
There is increasing interest in using native prairie plants for revegetation and pasture in the drier regions of the Canadian prairies. An experiment was conducted to determine the effects of simulated dry conditions and temperature on seed germination of side-oats grama grass (Bouteloua curtipendula (Michx.) Torr.). Over a 21d period, germination was studied in five growth chambers with constant temperatures of 15, 20, 25, 30 and 35°C and water potentials of –1.2, –0.9, –0.6, –0.3 and 0.0 MPa at each temperature. Seeds used in the study were bulk harvested seeds from a nursery established from 12 collections across Canadian prairie. More than 85% of the seeds germinated within 5 days at water potentials of 0.0 or –0.3 MPa when temperature was 25-35°C, but the percentage was reduced in solutions of lower than –0.6 MPa. Even though seed germination was reduced at lower water potential, 35% of seed germinated in a solution of –1.2 MPa, at 25-35°C. The final germination was highest at 25-35°C, intermediate at 20°C, and lowest at 15°C. Side-oats grama grass can germinate at low water availability, and if the growth condition is favourable, the majority of the seeds finish germination within a week. However, a temperature at or higher than 25°C is critical to improve total seed 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) | 0.001 | 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".