Effect of transportation distances, seasons and crate microclimate on broiler chicken production losses
Bibliographic record
Abstract
The goal of this research was to evaluate the microclimate (temperature, relative humidity and ECI-enthalpy comfort index) of commercial loads of broiler chickens at different transport distances: Dist15 (15 km on average) and Dist90 (90 km on average) in the summer and winter seasons and their effects on the production parameters body weight difference (BWD), mortality (%) and bruising prevalence (%). Twelve broiler loads were monitored using dataloggers to record temperature and humidity, with a total of 24 target crates per load. The experiment followed a factorial design [2 seasons (rainy and dry) × 2 distances (Dist15 and Dist90)] with a randomized complete block arrangement, 3 sexes (all males, all females, or mixed shipments) and one shipment per combination. BWD had a heterogeneous distribution throughout the load, and this distribution was not significantly correlated with the mean ECI measured during transport at 12 positions along the load. In terms of comfort, summer is the most critical period for broiler transport. In the interaction between rainy season and Dist90, the highest ECI was scored in the lethal zone (where physiological mechanisms are not enough to control body temperature). Mortality during the rainy season was not significantly different between distances. However, during the dry season, mortality was twice as high as broilers that travelled for 15 km. The prevalence of bruising on carcasses was not affected by the interaction between season and distance. As we know, broiler chicken performance, during transport, can be also related to road conditions, being hard to evaluate the real impact of seasons and distances on animal welfare. Load microclimate can compromise broiler chicken welfare during transport and it does not necessary reflect significant losses pre and post-slaughter.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".