Fatty Acid Composition of Backfat, Intermuscular, Kidney Pelvis and Heart Fat and Tail Fat of Angus Cross Steers Finished on Grass or High Grain Diets
Bibliographic record
Abstract
Fatty acid profiles of backfat (BF), intermuscular fat (IMF), kidney pelvic heart (KPH) fat and tail fat (TF) depots from 15-mo old Angus cross steers finished on grass (GS; n = 18) were compared to those finished on a grain diet (GN ; n = 14) to examine how diet and fat depot impacts fatty acid composition. GS steers grazed an average of 10 months (mo) on ryegrass and white clover irrigated pasture and GN finished steers were a corn based finishing diet for 4 mo. Overall, fat from GS steers contained higher percentages of C6:0 (P = 0.008), C12:0 (P = 0.003), C14:0 (P = 0.001), C16:0 (P = 0.002), C18:3 (P = 0.008), C20:0 (P < 0.001), C18:1 trans9 (P = 0.004), C18:2 cis9 cis12 (P < 0.001) and C18:2 trans9 trans12 (P < 0.001) than GN steers. Fat from GN steers contained higher percentages of C18:0 (P < 0.001). For both GS and GN steers, C18:0 content was higher in the KPH and IMF compared to BF and TF (P = 0.015) depots and C18:1 cis9 content was lower in KPH compared to BF and TF depots (P < 0.001). Therefore, fatty acid composition differs due to diet and differs across depots. Manipulating diets and source of fat (depot) could be used as strategies to modify the fatty acid composition of meat products to increase health benefits to consumers.
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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".