Bibliographic record
Abstract
Sled dogs undergo extreme metabolic demands during an ultra-distance race. These demands result in electrolyte derangements that can be associated with exertional rhabdomyolysis (ER). An observational cohort study was conducted during the 2019 Yukon Quest 300 race. Blood was drawn and will be analyzed to evaluate hormone concentrations (renin, aldosterone, ADH), and serum biochemistry with specific interests in creatine kinase, sodium, potassium, phosphorus and chloride concentrations. Urinalysis, including urine electrolytes, creatinine, and myoglobin (if collected during clinical presentation) will be investigated as well. Our specific aims in this study are to identify dogs with clinical ER in the field and compare their serum electrolyte status to those dogs dropped for other reasons and those completing the race. Ultimately, we aim to expand upon the hypothesis that electrolyte abnormalities, especially potassium depletion, may contribute or cause clinical ER in sled dogs as well as expand upon the mechanism underlying these electrolyte differences.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.019 |
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; both teacher heads agree on what is shown here.
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".