Reduction in turgid water volume in jack pine, white spruce and black spruce in response to drought and paclobutrazol
Bibliographic record
Abstract
Significant reductions in needle water content were observed in white spruce (Picea glauca (Moench) Voss), black spruce (Picea mariana (Mill) B.S.P.), and jack pine (Pinus banksiana Lamb.) seedlings in response to a 10-day drought, although turgor was apparently maintained. When the seedlings were re-watered after the drought, jack pine needles regained their original saturated volume, whereas white spruce and black spruce needles did not. Significant drought-induced reductions in turgor-loss volume (i.e., tissue volume at the point of turgor loss) were observed in shoots of all three species, especially jack pine. Repeated exposure to 7 days of drought or treatment with the cytochrome P(450) inhibitor, paclobutrazol ((2RS,3RS)-1-(4-chlorophenyl)-4,4-dimethyl-2-(1,2,4-triazol-1-yl)-pentan-3-ol), reduced seedling height relative to that of untreated controls in all three species. The reductions in saturated and turgor-loss needle volumes in the paclobutrazol-treated seedlings were comparable with those of seedlings subjected to a 10-day drought. The treatment-induced reductions in shoot and needle water contents enabled seedlings to maintain turgor with tissue volumes close to, or below, the turgor-loss volume of untreated seedlings. Paclobutrazol-treated seedlings subsequently survived drought treatments that were lethal to untreated seedlings.
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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".