Dynamic Characteristics of Tow Wheatgrass Species Seed Germination in Changing Temperature Condition
Bibliographic record
Abstract
The germination of seeds is crucial for protecting sandy plant and population dynamics.The research used the wild Agropyron michnoi and cultivated Agropyron cristatum widely distributed in sandy land as research object to study the Dynamic Characteristics of Seed Germination in changing temperature condition.The results indicated that both A.michnoi and A.cristatum had the highest germination rate at 25 ℃ and an Arabian continuous curve.Over 25 ℃,the germination rate of A.michnoi was higher than that of A.cristatum,when it was below 25 ℃,the outcome was different.Their germination index was all decreased step by step with the extension of incubation period.Seed germination of A.michnoi extended 25 days,while that of A.cristatum was nearly 22days.Changes of germination index pattern was clearly,in the first-phase A.cristatum was distinctly higher than A.michnoi,when in the mid-time,A.michnoi was significantly greater than A.cristatum,but in the late states,there was no marked difference between the two.Accumulating germination rate of A.michnoi was slowly increasing with the extension of incubation period,while that of A.cristatum was growing fast during the initial period of germination,then stable state was reached.The germination rate for both of them approached a climax at the third day,yet the germination rate of A.michnoi was much lower than that of A.cristatum.
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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".