Study on Breaking Methods for Hard Seed of Rare Species Ormosia xylocarpa
Bibliographic record
Abstract
For explore the breaking methods for hard seed of Ormosia xylocarpa,taking the Ormosia xylocarpaas materials,we made the experiments of acid etching in different time and soaking in different hot water temperatures,and analyzed the effect of different treatment on water absorption characteristics,germination,seed coat permeability and biochemical substances of Ormosia xylocarpa seed.The results showed that the imbibition rate of Ormosia xylocarpaseeds increases with acid etching time lengthen and soaking temperature raised.Acid etching was superior to hot water soaking in improve inhibition rate and germination indices.Higher germination indices and dehydrogenase activity were observed in group of 10 minutes-acid etching,with lower content of soluble sugar,MDA and conductivity.So we think that 10minutes-acid etching may improve seed vigor and promote germination.It may be the most efficient method for breaking hard seed of Ormosia xylocarpa.
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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 | 0.001 |
| 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".