Short communication: A comparison between two glucose measurement methods in beef steers during a glucose tolerance test
Bibliographic record
Abstract
Glucose tolerance tests (GTT) are commonly performed in beef cattle to evaluate the glucose-insulin signaling pathway. Blood samples are obtained via a catheter and then transferred back to the laboratory for further analysis. A hand-held glucometer used chute-side can make performing GTT's and quantifying blood glucose concentration much easier and faster for research purposes. The purpose of this study was to evaluate the agreement between a hand-held electronic glucometer (Precision Xtra; Abbott Diabetes Care Inc., Mississauga, ON, Canada) for chute-side use in beef cattle compared with a colorimetric assay in the laboratory (Stanbio Glucose LiquiColor; Stanbio Laboratory, Boerne, TX, USA). A GTT was performed on 13 Simmental × Angus steers during the growing phase. Blood samples were obtained via a jugular catheter. Glucometer readings were taken immediately after blood was sampled from the jugular with no preservative, and laboratory measurements were conducted on plasma preserved with sodium fluoride. A paired t-test (P = 0.40), Pearson's correlation (P < 0.001; r = 0.95), Bland-Altman plot, and Lin's concordance correlation coefficient (LCCC = 0.90) were completed to evaluate the performance of the glucometer relative to the results from the laboratory assay. Based on the results, we conclude that the glucometer is an acceptable method for measuring blood glucose concentration in beef cattle under field conditions.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".