Oxidation of U‐13C‐α‐linolenic acid is independent of body weight in pigs fed flaxseed diets
Bibliographic record
Abstract
Twelve pigs (14.6±0.41 kg initial body weight, BW; 4 pigs per treatment) were used to assess the effect of BW and cumulative intake of flaxseed (FS) on the oxidation of α‐linolenic acid (ALA). Pigs were fed FS free (CON) or FS diets according to three feeding regimes: R1, 10% FS diet from 15 to 37 kg BW; and then 5% FS diet; R2, CON from 15 to 37 kg BW; and then 5% FS diet; and R3, 10% FS diet form 15 to 37 kg BW; and then CON. At 25 and 55 kg BW, a single bolus dose of U‐13C‐ALA (2.75 mg/kg BW) was fed and recovery of 13C in expired CO2 was quantified during 26 h to estimate oxidation. There were no interactive effects (P>0.10) of feeding regime and BW on ALA oxidation. There was no effect of previous FS intake on ALA oxidation at 55 kg BW (P=0.20; 8.0% for R1 and 4.9% for R2). Across BW, R1 tended to have higher mean ALA oxidation than R2 (P=0.06; 9.8 vs 5.1%), whereas mean oxidation was similar for R2 and R3 (P=0.94; 5.1 vs 5.7%). BW did not affect the oxidation of ALA (P=0.42; 7.0 at 25 kg and 5.6% at 55 kg BW); pigs on FS tended to have higher ALA oxidation than pigs on CON (P=0.07; 8.0 vs 4.7%). ALA oxidation was generally less than 10% of intake, not affected by BW and previous nutrition, and reduced when feeding low ALA diets. Grant Funding Source : Ontario Pork, OMAFRA, AAFC
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".