Phase behavior of a binary lipid shortening system: From molecules to rheology
Bibliographic record
Abstract
Abstract The phase behavior of fully hydrogenated canola oil in soybean oil was investigated using iso‐solid lines from temperature‐controlled pulse‐NMR along with DSC data, with the rate of cooling of crystallized samples kept constant. The molecular diversity within the fat system was investigated using HPLC and GC. The microstructure of the fats was determined using a temperature‐controlled polarized light microscope, and the polymorphism of the solidified fat structures was determined via a temperature‐controlled X‐ray diffractometer. Hardness was measured by a temperature‐controlled Instron mechanical analyzer with a penetration cone. The phase behavior predicted by the DSC and iso‐solid lines did not account for the hardness trends observed, as the microstructure and polymorphism of the fat also played a significant role. The addition of hard fat to a system did not consistently increase the hardness of the fat system. Furthermore, the solution behavior demonstrated by the iso‐solid line diagram did not account for all trends in melting behavior, as both intersolubility and polymorphic changes occurred simultaneously. it was found that variations in hardness can be inferred from structural changes, although the structural level causing variation differs.
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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".