Bibliographic record
Abstract
To investigate the effects of aqueous extract of the red beet on loss anemia mice, the 50 mice were randomly divided into normal control group, model group and red beet water extract high, medium and low dose groups, each group contained 10 mice. The blood loss anemia mice model was constructed by the method of angular vein plexus. Gastric perfusion was started after 24 hours, whereas the mice in the control group were given the distilled water in the gastric. The number of red blood cells in mice and hemoglobin content were determined before the loss of blood, blood loss after 24 hours, after dosing 5 days and 10 days, respectively.Our model reduced the number of red blood cells in mice, and decreased the content of hemoglobin. After treated by the aqueous extract of red beet orally, the red blood cell count and hemoglobin content of mice increased variously. After gavaging 5 days with red beet aqueous extract, there was significant difference between the hemoglobin content, red blood cell count of the high dose group and the control group. The former group was significantly higher than those in control group. Red beet aqueous extract of high, middle dose group mice returned to normal after 10 days of gavaging. Aqueous extract of red beet hemorrhagic anemia could promote recovery.
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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 | 0.001 | 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".