Evaluation of an infrared thermography camera for measuring body temperature in dairy calves
Bibliographic record
Abstract
The objective of this diagnostic accuracy study was to validate an infrared thermography (IRT) camera and its software (FLIR One, FLIR, Global) for accuracy and precision for ocular temperature readings to serve as a proxy for rectal temperature in commercially housed calves. A total of 318 male Holstein calves were enrolled into this study from the day of arrival to a calf rearing facility until 14 d later. Researchers took an ocular temperature reading using an IRT camera, and a rectal temperature on each calf each day in the morning. The reference standard method for body temperature in the calves was rectal temperature. We assessed the data for agreement between the IRT and the reference standard using Pearson correlations by calf (accuracy), coefficients of determination (precision), and Bland-Altman plots for bias. In addition, a logistic regression model was built using the reference method as the outcome, with IRT as an explanatory variable to assess the diagnostic accuracy of IRT as an indicator of fever (rectal temperature ≥39.5°C). There was a negligible correlation between the IRT readings and rectal temperature (r = 0.22) and the coefficient of determination for IRT to predict rectal temperature was negligible (R 2 = 0.05), suggesting poor precision. The average mean difference between the IRT data and rectal temperature was 0.55°C, and the differences between IRT and rectal formed a linear line around the mean difference, suggesting the Bland-Altman analyses showed proportional error and bias. The optimal probability cut-off for IRT readings for fever was at 39.5°C, and had a receiver operating characteristic area under the curve of 0.67, a sensitivity of 61%, a specificity of 71%, and 78% (3,134/4,427) of the samples were correctly labeled as either having a fever or not using IRT readings. In summary, the IRT camera and software were not validated for serving as a proxy for rectal temperature in commercially housed calves due to poor precision, and proportional error partially explained by ambient environmental conditions. We suggest that this infrared thermography system should not replace rectal temperature readings for use in commercially housed calves.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".