VARIATION OF ELECTROLYTES, AMINO ACIDS AND REDUCING SUGARS IN COCONUT WATER OF DIFFERENT AGES FROM AN INLAND REGION OF BANGLADESH
Why this work is in the frame
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Bibliographic record
Abstract
Coconut water, extracted from the fruit of Cocos nucifera L., is a popular drinks throughout the tropics. The variable nature of the composition of the drinks had been established multiple times before, with regards to age, location and genetic variation. However, in Bangladesh, such studies were not carried out before. Thus, this study aims to compare electrolytes, amino acids and carbohydrates concentration in coconut water of different age collected from an inland region of the country. To determine electrolyte concentration atomic absorption spectrophotometry and Mohr titrimetric method were applied. Determination of carbohydrate and amino acid concentration required two separate high performance liquid chromatography (HPLC) methods. Regarding electrolytes concentration, rise of potassium, calcium and chloride ion concentration and fall of sodium and magnesium ion concentration were apparent. Potassium ion was the most abundant cation (50.88-67.56 mEq/L) while steep rise of magnesium ion concentration from 4 month to 6 months (4.140.17 to 12.722.52 mEq/L) was observed. Fructose and dextrose concentrations also escalated with coconut age. Amino acid concentrations varied as well. Histidine (0.43 g/100ml), arginine (0.053 g/100ml) and arginine (0.142 g/100ml) were the most abundant amino acids found in water 4, 6 and 8 months old coconuts. Overall, the trends of variation of components show intake of coconut water can bring different physical outcomes to different consumers and therefore, must be chosen carefully for patients with electrolytic imbalance and other medical complications.
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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) | 0.000 | 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) | 0.000 | 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