Bibliographic record
Abstract
INTRODUCTION In preparation for the most unfavorable weather, a plant may need special protection against the climate. These periods of recurring poor growing conditions must be anticipated well in advance. It would be no use for the plant to begin preparing for winter, for example, the morning of the first frost or for a long, dry, hot season in a desert when water was no longer available. What a plant does in preparation for long periods of poor weather is often quite elaborate, requiring a long period of good weather after the signal is received that an unfavorable season is approaching. The signal received by the plant cannot be linked directly to future poor conditions. For example, it is not low temperature which triggers the processes inside a plant leading to preparations for winter. Preparations might begin in mid to late summer when the temperature is still high. Shortening day length is a more reliable signal than temperature for plants to use to anticipate winter. SURVIVAL STRATEGIES Winter buds When forming winter buds a plant stops producing new leaves. Instead, small, tough scales are formed which tightly enclose the soft, delicate growing points in terminal buds on branches. They can withstand freezing and thawing many times over without disintegrating and they repel water while keeping the tender tissues inside moist and alive. Only in the spring, when their task is complete, are they shed as the growing points begin once more to grow.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".