Phase Space Analysis of Pig Ear Skin Temperature during Air and Road Transport
Bibliographic record
Abstract
High or variable ambient temperature can affect thermal regulation in livestock, but few studies have studied thermal variability during air and road transport, partly due to the lack of tools to compare thermal data from a long time series over periods of different duration. In this study, we recorded the ear skin temperature (EST) of 11 Duroc breeder pigs (7 females and 4 males) during commercial intercontinental transport from Canada to Spain, which included both road and aircraft travel and lasted 65 h. The EST was measured using a logger placed inside the left ear. Phase space diagrams EST, that is EST time series vs. itself delayed in time, were used to quantify the variability of the time-temperature series based on the areas that included all the points in the phase space. Phase space areas were significantly higher for all the animals during air travel, almost doubling that of road transport. Using the phase spaces, we identified an event during air transport that lasted 57 min, leading to a general decrease in EST by 8 °C, with respect to the average EST (34.1 °C). We also found that thermal variability was more stable in males (F = 20.81, p = 0.0014), which were also older and heavier.
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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 | 0.000 | 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".