Cold blood perfusion for selective hypothermia in acute ischemic stroke
Bibliographic record
Abstract
Hypothermia is the most reliably effective neuroprotectant, and yet systemic complications limit application. A large body of animal data suggests that hypothermia is effective for focal cerebral ischemia, namely acute ischemic stroke. In order to apply hypothermia effectively, a selective approach is required to maximize the effect on the brain while minimizing systemic side effects. Due to poor transferability of promising findings in rodent models to human clinical trials for neuroprotection, the focus of this review is large animal gyrencephalic models. Unlike rodent data which favor mild hypothermia, the majority of large animal studies on selective hypothermia support moderate-to-deep hypothermia (<30°C). Cold blood perfusion produces the rapid rate of temperature reduction and depth of hypothermia required to produce meaningful neuroprotection. Further studies of selective hypothermia in acute ischemic stroke require attention to duration and rate of cooling to optimize the neuroprotection offered by this technique.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".