Monitoring Pathogen‐Induced Sickness in Mice and Rats
Bibliographic record
Abstract
Sickness behavior monitoring, a technique for examining the development of sickness symptomatology following infection, is necessary in experiments studying neurochemical and physiological changes associated with pathogen-induced immune activation. However, the results of sickness behavior monitoring are difficult to reconcile due to inconsistencies in protocol methods and rater bias. The protocol described herein offers a non-invasive and unbiased approach to assess the progression of pathogen-induced sickness behaviors. This simple, straightforward method uses a five-point scale to assess animals for the presence of four sickness behaviors (i.e., '"0" = no sickness behaviors; "4" = four sickness behaviors) at various time points following exposure to a pathogen. This approach removes the ambiguity and bias inherent to other methods of sickness behavior monitoring that rely on subjective ratings of severity for individual symptoms. This protocol has been successfully applied to male and female rodents injected intraperitoneally with lipopolysaccharide and polyinosinic:polycytidylic acid, and has been effective in pubertal and adult populations. Protocols for changes in body temperature and weight are also provided as physiological markers of sickness. © 2017 by John Wiley & Sons, Inc.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".