Compositional analysis of dairy fats, phospholipids and positional distribution on TAG from cows fed fish meal
Bibliographic record
Abstract
DHA enriched milk fat samples obtained at the University of Guelph from cows fed fish meal (FM) were characterized and compared with milk from cows fed corn/soy silage. The total FA was analyzed by GC equipped with 100m CP Sill 88 capillary column by which more than 100 FA were identified. Ag +-TLC combined with GC was used to analyze all possible positional cis and trans monoenes. GC and Ag+-HPLC was used to resolve all CLA isomers. 9c11t, 18:2 was the major CLA isomer found in both diets. The other major CLA isomers were 9t11c and 7t9c; the former was identified by GC, and the latter by Ag+-HPLC.;The TAG and PL were separated using Supelco LC-Sil columns. PL were analyzed and distributed into three major classes: PC, PE and SM. SM was the most saturated PL fraction (ca. 70%). There was an increase in the degree of unsaturation of the analyzed PL in the following order PE> PC> SM. The CLA content in the major PL was lower than in TAG.;Positional analysis of TAG was performed enzymaticaly and using Grignard reactions. The MAG were isolated on boric acid impregnated TLC plates and analyzed as their butyl esters by GC, which was confirmed by GC-MS. The distribution of short chain-FA was found in both sn-1,3 and sn -2 positions. For FM samples, C12:0, C16:0 and C18:0 FA were predominantly at sn-1,3 position.;The inclusion of FM into diets of dairy cows resulted in an increase of DHA (0.04 to 0.17%). Increases were also observed for 9c11t-CLA (0.39% to 0.66%), 7t9c-CLA (0.05% to 0.26%), and 9t11c-CLA isomers (0.05 to 0.13%). 10t-18:1 increased (0.57% to 4.58%) and 11t-18:1 decreased (1.16 to 0.96%).
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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 | 0.001 | 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".