Bibliographic record
Abstract
In excessive manner, mangan (Mn) as an essential nutrient can be toxic to the plant. This phenomenon often occurs in acid soil. Hence, it is needed gene resources to develop plant in acid soil. The soybean germplasm tolerance to Mn toxicity was tested in seed laboratory, using two factors experimental design. The first factor was Mn toxicity containing two treatments (1) 0 ppm Mn in pH 7 as control, and (2) solution concentration of 75 ppm Mn in pH 4. The second factor was 14 accessions of soybean germplasm. Results showed that generally root characters decreases while shoot characters increased in Mn toxicity condition. However, some genotypes showed different performance. There was one genotype having the highest root dry weight in Mn toxicity condition, i.e. MLGG 0091. The highest root dry weight in this genotype was also supported by the root length and number of roots. MLGG 0091 was also capable to increase the length epicotyle that contribute to the increase in seedling dry weight. Therefore MLGG 0091 can be used as a gene source for tolerance to Mn toxicity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".