Oxalate Content of Stir Fried Silver Beet Leaves (Beta Vulgaris Var. Cicla) with and without Additions of Yoghurt
Bibliographic record
Abstract
Total and soluble oxalic acids were extracted and analysed by HPLC chromatography following Asian cooking methods, which involved soaking, boiling and stir frying of silver beet (Beta vulgaris var. cicla) leaves. Autumn-grown silver beet leaves contained 1658 ± 114 mg/100 g dry matter (DM) of total oxalates, 954 ± 49 mg/100 g DM of soluble oxalates and 704 ± 98 mg/ 100 g DM insoluble oxalates. Soaking and boiling before stir frying reduced the soluble oxalate contents to a mean of 455 mg/100 g DM. Addition of standard or low fat yoghurt following the pre-treatments of soaking, boiling, stir frying and soaking, boiling and stir frying further reduced the soluble oxalate content to a mean of 190.8 ± 49.8 and 227.5. ± 47.0, respectively, for the standard and low fat yoghurt mixes.
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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) | 0.002 | 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".