Effects of Combined Lead and Cadmium on Seed Germination,Seedling Growth and Leaf Photosynthetic Pigment Contents of Brassica Juncea
Bibliographic record
Abstract
Taken combined lead and cadmium as variable value,the brassica juncea's seed germination experiment of eight treatments which had three repeats were designed to study the effect of combined lead and cadmium stress on the seed germination,seedling growth and photosynthetic pigment contents of B.Juncea.The result showed that the germination vigor,germination rate,relative germination rate,germination index,relative germination index,vigor index,relative vigor index,seedling height,root length,root number of B.juncea decreased obviously with the increasing of combined lead and cadmium concentration,low concentration of combined lead and cadmium was better for the accumulation of fresh and dry weight of seedling,but the high concentration of combined lead and cadmium could restrain their accumulation.It came to a dicision that the combined lead and cadmium wasn't better for seed germination and seedling growth of B.juncea.In addition,low concentration of combined lead and cadmium would help to accumulate the cotyledon photosynthetic pigment contents of B.Juncea,but the high concentration of combined lead and cadmium could stop the synthesis of cotyledon photosynthetic pigment of B.Juncea.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".