Some factors influencing the level of reducing sugar in the blood of black-tailed deer
Bibliographic record
Abstract
Some of the factors that influence the blood reducing sugar level in the black-tailed deer Odeeoileus hemionus columbianus (Richardson) (Vancouver Island genotype), have been investigated. The distribution of reducing sugar in the blood of these animals was also examined. It was found that: feed intake during the hour preceeding blood letting, short periods of fast, nature of the feed, and sex of the animal apparently have no effect on the level of blood reducing sugar in deer. Blood samples taken in the evening generally had a higher reducing sugar level than those taken earlier in the day. The means used to restrain the animals during the blood letting procedure was also found to have a marked influence on the level of blood reducing sugar. Deer restrained by physical force exhibited significantly higher and more variable blood sugar levels than those immobilized with succinylcholine. The length of time required to draw a blood sample from an animal also influenced the blood sugar level. The longer the time to let a sample, the higher the blood sugar level in the sample. The results indicate that the degree of excitement, fear, and pain experienced by the animals preceeding and during the blood letting procedure was the principal cause of variability found in the level of blood reducing sugar. No reducing sugar could be detected in the erythrocytes of these deer.
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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 | 0.000 |
| 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".