Bibliographic record
Abstract
Heat stroke is caused by the inability to dissipate accumulated heat. In dogs, it is characterized by core temperatures above 41⁁°C (105.8⁁°F) with CNS dysfunction. It results from exposure to a hot and humid environment or from strenuous physical exercise. Activation of inflammatory and hemostatic pathways initiates a systemic inflammatory response syndrome which often progresses to multiorgan dysfunction syndrome. Serious complications of heat stroke include rhabdomyolysis, acute kidney injury, acute respiratory distress syndrome, and disseminated intravascular coagulation. Several environmental and physiological factors are associated with the risk of developing heat stroke. These include high environmental temperature and humidity, lack of acclimation and fitness, obesity, body weight (>15⁁kg), breed (e.g. Labrador and golden retrievers, brachiocephalic breeds), hormonal diseases (e.g. hyperthyroidism, pheochromocytoma, and insulinoma), upper airway obstruction (e.g. laryngeal paralysis), seizures or significant muscle activity, and malignant hyperthermia. The most common clinical signs of canine heat stroke include collapse, tachypnea, spontaneous bleeding, shock, disorientation/stupor, seizures, and semi-coma/coma. Despite appropriate cooling and supportive treatments, mortality rates above 50% have been reported in humans and canines suffering from heat stroke, because no specific treatment is available to ameliorate the activated inflammatory and hemostatic pathways.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".