Characterizing the literature surrounding transportation of young dairy calves: A scoping review
Bibliographic record
Abstract
Transportation is a stressful event for cattle, as it may involve various handling practices, commingling, deprivation of food and water, and fluctuating temperatures. Calves are particularly susceptible to these stressors because their physiological and immune systems are still developing. There has been no formal synthesis of the scientific literature evaluating the effect of transportation on young dairy calf health and performance; the aim of this scoping review is to describe and characterize this body of work. We targeted both descriptive and analytic studies examining transport of calves, including listing how the effect of transport has been evaluated. Eight databases were searched for relevant articles with eligible studies being primary research articles investigating transportation of calves of either sex who were younger than 60 d of age or weighed less than 100 kg. Two reviewers independently screened the title and abstracts of 6,859 articles with 361 potentially relevant articles screened at full text. Of these, 46 were relevant and had data extracted. Articles reporting study location were conducted in the United States (n = 5), Australia (n = 3), Japan (n = 3), and New Zealand (n = 3). Common transport-related variables evaluated included time in transit (n = 13), distance of transportation (n = 8), vehicle-related factors (n = 8), and age at time of transportation (n = 4). Outcome measures varied greatly, including blood parameters (n = 28), health assessments (n = 20), weight (n = 17), behavioral metrics (n = 14), mortality (n = 7), feed intake following transportation (n = 4), salivary cortisol concentrations (n = 3), morbidity (n = 3), and isolation of Salmonella Dublin in fecal samples (n = 2). Outcome parameters were measured during transport or ranged from immediately after to one year following transportation. As the transport-related risk factors and outcomes measured assessed varied widely between studies, future quantitative synthesis (e.g., meta-analysis) in this area may be limited. Several knowledge gaps were identified, including methods to prepare calves for transportation, such as improving nutrition, administering medication, or transporting calves at an older age or weight. Further research could also focus on consistent and clear reporting of key items related to study conduct and analysis, as well as the development of a core outcome set for calf transport studies.
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 | 0.018 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.031 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".