The Study of an Animal Fever Model Using Endotoxin and Its Standardization in Rabbits
Bibliographic record
Abstract
Objective To determine the effect from different doses of LPS,the temperature and humidity of the ambient, rabbits restraining conditions and physical functions on rabbits febrile response.Method Intravenous application of endotoxin (ET) is a traditional method to construct an animal fever model.The key factor is to find the optimum dosage.The fever was studied after different doses of ET were intravenously injected (Ⅳ). Results and conclusion the results of the study showed:1)The increase of LPS dosage had a promotive effect on the febrile response of the rabbits with shorter latency to onset,higher peak fever change, longer duration and greater temperature response index (TRI).2) The rabbits developed a positive dose\|dependent fever in response to ET over the range of 0.5?ng/kg\|2000?ng/kg.Small doses (0.5?ng/kg,2?ng/kg)of ET induced a monophasic fever and large doses (20?ng/kg,100?ng/kg,200?ng/kg,2000?ng/kg)of ET induced a biphasic fever.In response to the doses of 100?ng/kg and 200?ng/kg the rabbits developed a homogeneously typical biphasic fever.Therefore,the recommended range of ET dose is from 100?ng/kg to 200?ng/kg in making a rabbit fever model.The results shows that (25±1)℃ ambient temperature is better than (18±1)℃ and the neck stock is better than the prone stock.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".