Effects of Temperature and Photoperiod on the Extension Growth of Six Temperate Grasses
Bibliographic record
Abstract
In western Canada late season pasture yields vary considerably among species. During August and early September yields of Bromus riparius and Dactylis glomerata are double that of the more commonly grown Bromus inermis (Knowles and Sonmore, 1985). The importance of leaf area to crop growth rate pnor to canopy closure is well documented (Rhodes, 1973). Two components of leaf area are the final size of leaves and the rate of leaf appearance, with final size of leaves largely dependant on the rate of extension and duration of extension (Edwards, 1967). Since the maturity of a leaf is closely associated with the emergence of a new leaf there is a close association between rate of appearance and duration of extension (Edwards, 1967). Considerable variation has been shown among and within species for stem extension, leaf extension rate and rate of leaf appearance or duration of extension in response to temperature and photoperiod (Ryle, 1966; Nelson et al., 1978; Heide et al., 1985). Variations among species for late season productivity may be related to the influence of a declining temperature and photoperiod on leaf area and canopy development. The objectives of this study were to examine the extent to which and the mechanisms whereby temperature and photoperiotl affect leaf and stem extension of several grasses commonly grown m western Canada.
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 | 0.001 | 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".