CHEMICAL COMPOSITION AND OPTICAL PROPERTIES OF REFINED SUNFLOWER OIL WITH ADDED VARIOUS OILS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Some physicochemical characteristics and elemental composition of refined sunflower oil, as well as linseed oil added to it, were investigated; linseed oil and olive oil; truffle oil and rosemary oil. Fatty acid analysis shows substantial increases in monounsaturated fatty acids with the addition of truffle and rosemary oils (up to about 78 %). With the same supplements, a significant oxidative stability over 20 hours was also observed. High concentrations of chlorophyll were found with the addition of rosemary oils and oils of linseed oil and olive oil. β-carotene was affected three to six times in all supplements compared to the commonly refined oil. Eight elements (Mg, Cr, Mn, Zn, Ni, As, Pd and Cd) were analyzed in the studied oils, no presence of toxic elements As and Cd (< 0.02 mg kg-1), lead was up to 0.04 mg kg-1. The remaining elements vary in different concentrations depending on the additive oils used. The fluorescence spectra of the tested samples were obtained for excitation wavelengths of 380 nm, and the fluorescence maxima allowed to determine the relationship between the optical and chemical properties of the samples. In addition, infrared spectroscopic experiments (ATR and transmittance) were used to investigate the fatty acid profile of the analyzed oil samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it