Digestive Discomforts and Effect of Ingested Food in People Performing Hajj
Bibliographic record
Abstract
A variety of health issues have been investigated in the Hajj pilgrims (HPs) in KSA. However, it is still obscure to decide which meals contribute to health related issues specifically gastrointestinal disorders and allergies. Hence present study was planned to compare the effect of using different meals on GIT disorders and allergies. The data was categorized into two groups. Group 1 of age matched HPs comprised a Functional Digestive System Questionnaire (FDSQ) to study digestive disorders. Group 2 HPs were compared for those received Toafa Corporation Meals (TCM) and those did not received Toafa Corporation Meals (NTCM). The FDSQ showed some of the gastrointestinal symptoms in male and female Hajj pilgrims differing significantly (p<0.05). The efficacy of the treatment was evaluated by subject recovery scoring (SRS). The 61.7% HPs taking TCM revealed various discomforts and food allergy and the 50.6% HPs using NTCM did not suffer from any disorders. However, the pilgrims taking the meals provided by the Toafa corporation but not showing allergy were more significant in number (p=0.0002). The existing study presents a new method (construction of a FDSQ) for comparing gastrointestinal and other disorders. The present study recommends that Toafa Corporation should provide suitable meals for thepilgrims to meet their actual needs during Hajj and health situation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".