Can alternating temperature, moist chilling, and gibberellin interchangeably promote the completion of germination in <i>Clematis vitalba</i> seeds?
Bibliographic record
Abstract
Each plant species has particular requirements for seed germination, and some of them respond differently to constant or alternating temperature regimes. In this study, the interchangeable effects of different treatments and temperatures on the completion of seed germination of Clematis vitalba L. were investigated. The seeds were tested with a constant (from 5 °C to 25 °C) or a fluctuating (25/10 °C) temperature regime, and the effect of gibberellic acid (GA 3 ), incubation at warm (W) or cold (C) temperatures while being imbibed, and drying after ripening (DAR) were evaluated. The final germination percentages and the time in days required to reach 50% of germination (T 50 ) were calculated. GA 3 and C significantly enhanced completion of seed germination at all of the temperatures tested. A strong positive effect of alternating temperature was observed, which triggered completion of seed germination regardless of treatment. Under the fluctuating temperature, the chilled seeds had the most rapid germination. Low germination rates were observed for both control and DAR treatments. Seeds of C. vitalba display a certain degree of dormancy, which can be broken by moist chilling and GA 3 treatments. Moreover, alternating temperature stimulates the completion of seed germination by satisfying certain physiological requirements for germination under constant temperatures.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".