Effects of Simulated Acid Rain on Seed Germination and Seedling Physiological Characteristics of Medicago Sativa L.
Bibliographic record
Abstract
Using the seed of Medicago Sativa L.as material.We studied the effect of different pH simulated acid rain on the seed germination and seedling physiological characteristics of Medicago Sativa L.The experiment tested the germination power,germination rate,germination index,vitality index,seedling fresh weight,root length,bud length,chlorophyll content of seedling leaf and permeability of plasma membrane etc targets.The results of the test indicated that the germination power,germination rate,germination index and vitality index all decreased with the simulated acid rain density increased.There were great changes among the indexes of seedling growth increment:seedling fresh weight and root length increased with simulated acid rain pH rising,while bud length decreased with simulated acid rain pH increasing.The results indicated that bud growth was restrained by simulated acid rain.And permeability of plasma membrane decreased with the acid rain pH increasing,which showed that seedling leaves were destroyed by the acid rain.With simulated acid rain pH going up,the chlorophyll content of seedling leaf enlarged.The experiment proved that the seed of Medicago Sativa L.under the condition of weak acid(pH≥4.0) can normally sprout and growth,and has certain acid-tolerance.But under the condition of strong acid(pH≤3.0) seed germination and seedling growth were seriously restrained by simulated acid rain.
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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".