Repeatability and reproducibility of measurements obtained by dual-energy X-ray absorptiometry on pig carcasses1
Bibliographic record
Abstract
The precision of a dual-energy X-ray absorptiometry (DXA) device in terms of repeatability and reproducibility was evaluated on nine left half-carcasses from pigs with large variability in body weight and fat content. Repeatability was assessed by scanning each carcass 10 times sequentially in the same position. Reproducibility was assessed by scanning each carcass in 10 different positions. Images were analyzed with DXA software using a custom region of interest (ROI) and the standard head, trunk, arm, and leg ROI. Predicted values from the DEXA for bone mineral content (BMC), bone area, bone mineral density (BMD), total weight, soft-tissue weight, fat-tissue weight, and lean-tissue weight were considered. Repeatability was associated with the variance between measurements on the same carcass in the same position (repeatability conditions). An average variance value was obtained with all the carcasses combined, and the SD was calculated as the square root of this combined variance. The CV was the ratio between the SD of the measurements and its average value. Reproducibility was calculated for each carcass as the difference between the variance obtained under the reproducibility conditions and that obtained under the repeatability conditions. The effects of the ROI and conditions were evaluated by ANOVA and Tukey's test. Means of BMC, bone area, BMD, fat tissue, and lean tissue differed among the ROI (P < 0.05) in both the repeatability and reproducibility conditions. The CV of DXA measurements under repeatability condition obtained in the head, arm, and leg ROI was lesser than 1%. Only the repeatability errors of fat tissue differed (P < 0.05) among the ROI, with the lowest precision found for the trunk ROI. The reproducibility errors of BMC, bone area, fat tissue, and lean tissue differed (P < 0.05) among the ROI. The custom ROI had reproducibility errors greater than 2% for fat tissue and greater than 3.5% for BMC and bone area. In addition, the trunk ROI had the highest reproducibility errors for fat tissue (20.7%) and lean tissue (6.2%) when compared to the other ROI. In conclusion, repeatability and reproducibility results obtained for most of the studied ROI indicate that DXA is a valuable tool for carcass evaluation. From a methodological viewpoint and considering the variations observed in this study, the ROI should be chosen based on the item to be evaluated or on the conditions in which the DXA measurements are to be taken.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".