Glucose and hormonal profiles of Meishan-derived and Large White gilts in early and late gestation
Bibliographic record
Abstract
Jugular catheters were inserted non-surgically in eight Large White (LW) and nine Genex-Meishan (GM, with 50% Meishan genes) gilts on days 37 and 106 of gestation to obtain serial blood samples on days 38 and 107. Meal time was 0805. Three preprandial samples (baseline) were obtained at 0740, 0750 and 0800 as well as samples every 20 min thereafter until 1100. Glucose and insulin concentrations were measured in all samples and values for cortisol and insulin-like growth factor-I (IGF-I) were determined on preprandial samples and hourly samples thereafter. All gilts were weighed and their backfat thickness measured at mating and on days 17, 34 and 109 of gestation. Gilts of the GM line were lighter (P = 0.03) and fatter (P = 0.004) than LW. Postprandial values for cortisol and IGF-I were greater in GM than LW gilts in early gestation only (P < 0.05). The same was true for baseline IGF-I (P < 0.001). Postprandial insulin was not affected by breed or stage of gestation (P > 0.1), yet glucose values were greater in LW than in GM gilts (P < 0.05) and postprandial glucose was greater in late compared to early gestation in both breeds (P < 0.001). In conclusion, both cortisol and IGF-I concentrations varied differently between genotypes depending on the stage of gestation. Furthermore, even though postprandial insulin was not affected by breed, concentrations of glucose were lower in GM gilts. A metabolic adaptation to gestation was observed in both breeds, with glucose values increasing in later gestation. Key words: Meishan, Gestation, Pigs, Hormones, Insulin, Glucose
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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".