Bibliographic record
Abstract
Taking Arctium lappaas material,the effect of different Pb solution concentrations on seed germination and seedling growth of Arctium lappawere studied.The results showed that the seed germination rate was the highest at the 150mg/L Pb2+solution concentration;Pb stimulated the seed germination at 50mg/L and 150mg/L concentrations,and restrained the seed germination at the higher concentrations(150 mg/L).All the seed germination potential,germination index,and vital index,as well as the seedling fresh weight showed out low-high-low tendency,and the crest value were at the 150mg/L Pb2+solution concentration except the seedling fresh weight.The root and bud lengths of seedlings showed out the same tendency as the seedling fresh weight,but the crest values were at the 50mg/L and150mg/L Pb2+solution concentration respectively.The malondialdehyde(MDA)content and chlorophyll content of seedling leaves increased with the Pb2+solution concentrations.The activities of SOD and POD also showed out low-highlow tendency,but they remained high levels under conditions of high Pb2+solution concentrations(600mg/L).The results indicated that Pb stimulated the seed germination and seedling growth of Arctium lappa at the lower concentrations,and restrained the seed germination at the higher concentrations,but Arctium lappa seed still had higher germination rate and seedling could also be normal growth at the high concentrations.SOD activity and POD activity under high solution concentration of Pb stress still had a highly reactive.Through its antioxidant system against adversity,Arctium lappahad a certain resistance to Pb stress.
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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) | 0.001 | 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".