Source–sink imbalance increases with growth temperature in the spring geophyte Erythronium americanum
Bibliographic record
Abstract
Spring geophytes produce larger storage organs and present delayed leaf senescence under lower growth temperature. Bulb and leaf carbon metabolism were investigated in Erythronium americanum to identify some of the mechanisms that permit this improved growth at low temperature. Plants were grown under three day/night temperature regimes: 18/14 °C, 12/8 °C, and 8/6 °C. Starch accumulated more slowly in the bulb at lower temperatures probably due to the combination of lower net photosynthetic rate and activation of a 'futile cycle' of sucrose synthesis and degradation. Furthermore, bulb cell maturation was delayed at lower temperatures, potentially due to the delayed activation of sucrose synthase leading to a greater sink capacity. Faster starch accumulation and the smaller sink capacity that developed at higher temperatures led to early starch saturation of the bulb. Thereafter, soluble sugars started to accumulate in both leaf and bulb, most probably inducing decreases in fructose-1,6-bisphosphatase activity, triose-phosphate utilization in the leaf, and the induction of leaf senescence. Longer leaf life span and larger bulbs at lower temperature appear to be due to an improved equilibrium between carbon fixation capacity and sink strength, thereby allowing the plant to sustain growth for a longer period of time before feedback inhibition induces leaf senescence.
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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 | 0.000 | 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 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".