Germination of <i>Cenchrus ciliaris</i>, <i>Pennisetum divisum</i>, and <i>Panicum turgidum</i> is seasonally dependent
Bibliographic record
Abstract
Knowledge of optimal conditions for germination facilitates more efficient practices, such as fodder production and restoration. We assessed seeds of three grass species harvested in winter and summer 2018. Germination ability was assessed under two night/day temperature regimes (15 °C/20 °C, 20 °C/30 °C) and two photoperiod regimes (0, 12 h light per day). Winter-maturing seeds had a slightly lower mass and reduced germination. Temperature and light requirements for optimal germination were dependent on species and harvest-time. Summer-maturing seeds of all three species had higher germination rates regardless of germination temperature. Interactions among treatment temperatures and species were 0.7- to 5.4-times higher than the control, as shown by heatmaps. Therefore, attention to these factors will improve the efficiency of seedling establishment for rehabilitation work.
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) | 0.001 | 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 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".