Nutrient and hormone levels in Douglas-fir corrosion cavities, megagametophytes, and embryos during embryony
Bibliographic record
Abstract
Gymnospermous embryos are nourished by fluids secreted from the megagametophyte. During early embryony, these fluids occupy the newly formed corrosion cavity. We describe a novel method for extracting corrosion cavity fluid and provide chemical analyses based on extractions from approximately 120 000 Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) megagametophytes. Levels of potassium, phosphorus, calcium, zinc, and iron were higher in corrosion cavity fluid than in whole tissue, but levels of sulphur and manganese were lower. Levels of cyclitols, sucrose equivalents, erythrose, and arabinose were many-fold higher in corrosion cavity fluid than in whole tissues. Ala, Ser, Arg, Glx, and NH 3 exceeded 80 mmol/kg dry mass in corrosion cavity fluid. These levels were about 100-fold higher than those found in whole tissues. During early embryony, hormone levels in corrosion cavity fluid were higher than levels observed in whole megagametophytes by 120-fold for indole-3-acetic acid, 53-fold for abscisic acid, and 8- to 10-fold for cytokinins. Nutrient and hormone levels tended to be much higher in the corrosion cavity fluid than would have been predicted based on whole-tissue analyses. Dynamic changes in nutrient and hormone levels occurred over time in the corrosion cavity, and these changes may normalize embryony in situ.
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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) | 0.000 | 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".