Hypercholesterolemia Risk Related to Consumption of Palm Oil Produced in Côte d’Ivoire
Bibliographic record
Abstract
The purpose of this work is to determine the consumption pattern estimated from quantity and frequency of consumption of palm oil produced in Côte d'Ivoire in order to assess risk of hypercholesterolemia related to these oils. To achieve this objective, a cross - sectional survey was conducted with 417 randomly sampled people in seven district capitals of Côte d 'Ivoire. This investigation shows that average of crude and refined R1 and refined R2 palm oil consumed are 24.52 mL, 25.88 mL and 24.13 mL per person per day, respectively. In addition, datas on consumption frequency of different palm oils indicate that refined palm oils are most prevalent in population’s dishes. Daily consumption frequency of crude and refined palm oils varies between 7.43 % and 85.40 %. These oils contain 32.95 % to 48.04 % palmitic acid (hazard). For a bioavailability of 100 % palmitic acid, the risk assessment for hypercholesterolemia indicates that 26.02 %, 25.80 % and 21.73 % of surveyed populations ingest higher quantities of palmitic acid. Those are greater than the recommended rate Anses (National Agency for Food Safety, Environment and Labor) during consumption crude and refined palm oils. 26,020, 25,800 and 21,730 cases of increase in serum cholesterol per 100,000 inhabitants after consumption crude, R1 and R2 oils. Concerning a bioavailability of 11 %, risk of hypercholesterolemia is 0 %; 0.02 % and 0.03 % respectively for the consumers of crude, R2 and R1 palm oils. Hypercholesterolemia risk varies from the mode of consumption and oils types.
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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 | 0.000 |
| 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".