Herd-level prevalence of the ultrasonographic lung lesions associated with bovine respiratory disease and related environmental risk factors
Bibliographic record
Abstract
Bovine respiratory disease complex (BRD) is a major calf disease during the preweaning period. Thoracic ultrasound (TUS) has been recently described as a reliable tool for assessing BRD-associated lung lesions. The objectives of this study were to define the herd-level prevalence of lung consolidation assessed by TUS (CONSTUS). A total of 39 Québec dairy herds were randomly chosen to participate in this cross-sectional study. Between 6 and 12 preweaned calves were examined for signs of CONSTUS defined by any site with ≥3 cm consolidated lung tissue during 1 visit in summer and 1 visit in winter. Herd questionnaire focused on calf health and housing data [airborne bacteria (aerobic, coliform, yeasts and mold counts), air drafts, temperature, hygrometry, and ammonia levels] were also collected during these visits looking for potential association with CONSTUS prevalence. The median herd-level of CONSTUS prevalence (interquartile range) were 8% (0-22%) in summer and 15% (0-35%) in winter. Multivariable analyses showed that season was associated with an increased CONSTUS prevalence [10.0 vs. 19.3%; odds ratio (OR) = 2.16], as well as group housing during preweaned period (9.6 vs. 20.0%; OR = 2.37) and perceived BRD problem by the farmer (10.6 vs. 18.3%; OR = 1.89). Despite tremendous changes in calves' environment between winter and summer, none of the housing variables were associated with the CONSTUS prevalence in this study. Based on the observed CONSTUS prevalence ranges in the present study (herds in the lower prevalence quartile), an achievable goal of none of 12 calves with consolidation ≥3 cm can potentially be used to define a low-BRD risk herd.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".