THE EVALUATION OF QUALITY AND SENSORY CHARACTERISTICS OF MUFFINS MADE WITH COCONUT BUTTER
Bibliographic record
Abstract
Muffins are a sweet and baked item which is appreciated by people due to its sweet flavor and soft moist texture. The aim of our work was to study the effects of butter replacement with coconut butter on the physiochemical, sensory and quality characteristics of muffins. Butter is a main ingredient in baking goods however it has much adverse health effects like increasing bad cholesterol levels and risk of cardiovascular diseases due to high saturated fat content and cholesterol. Whereas coconut butter is much healthier as it is made from the super food coconut. It has got ample amount of lauric acid which aids in the stimulation of immunity and eradicates harmful bacteria, viruses, and funguses. It fosters metabolism which in turns reduces weight, adding to energy levels simultaneously. Essential amino acids, calcium, and magnesium are all a significant component of the coconut butter. It also provides us with healthy fats so that we feel nourished and fresh. The quality and acceptability of both muffins made with butter and those made with coconut butter were compared. The physical properties were determined using texture analyzer and calipers. A taste panel of 20 panelist showed that the replacement of butter with coconut butter in muffins did not affect the overall quality and acceptability of muffins.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".