Climatic and aeroallergen risk factors for chronic obstructive pulmonary disease in horses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To estimate the association between climate and airborne pollen and fungal factors and chronic obstructive pulmonary disease (COPD) in horses. SAMPLE POPULATION: Data from 1,444 horses with a diagnosis of COPD. PROCEDURE: The Veterinary Medical Database was used to identify records of horses admitted to veterinary teaching hospitals in the United States and Canada between 1990 and 1999. Rainfall, mean minimum and maximum temperature, and maximum monthly pollen and fungal spore (mold) counts recorded at the city closest to where the hospital is located were identified for each month data were reported to the Veterinary Medical Database. Associations between climatic and aeroallergen data and monthly prevalence of COPD were estimated by use of cross-correlation and logistic regression models. RESULTS: Significant positive correlations were found between prevalence of COPD and rainfall 3 months previously, minimum temperature 1 and 2 months previously, total pollen counts measured 3 months previously, and total mold counts measured during the same month and 1 month previously. CONCLUSIONS AND CLINICAL RELEVANCE: Outdoor aeroallergens and climatic factors may contribute to the occurrence of COPD in horses.
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.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it