Stress-induced fever after postischemic rectal temperature measurements in the gerbil
Bibliographic record
Abstract
Postischemic temperature, which modulates brain injury, is commonly determined via a rectal temperature (Trec) probe. This procedure causes a stress-induced fever (SIF) in rodents that may aggravate injury or diminish the efficacy of a neuroprotectant. We continually measured core temperature (Tcore) via an implanted telemetry probe and made 16 Trec measurements over 4 days in sham and ischemic gerbils (5 min bilateral carotid artery occlusion). Controls did not have Trec sampled, but Tcore was measured. Rectal temperature measurements predicted Tcore in sham and ischemic gerbils. The Trec measurements caused a SIF (1 degrees C peak) in shams that did not habituate, whereas the SIF was initially absent and then increased over days in ischemic gerbils. Ischemic groups had similar CA1 injury (approximately 32% remaining), presumably because Trec measurements only resulted in a significant SIF starting on day 2 postischemia, when cell death is less sensitive to hyperthermia. Caution is warranted with Trec measurements, since the resultant SIF occurs to different extents in normal and ischemic rodents. Furthermore, the SIF could vary according to many other factors, such as the type and severity of insult, the time and frequency of measurement, and drug treatment. Accordingly, postischemic Trec measurements should be replaced with telemetry probes.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".