Knowledge and Awareness of Saudi Public Regarding the Outbreak and Prevention of COVID-19 in Saudi Arabia; a Questionnaire-Based Study
Bibliographic record
Abstract
INTRODUCTION: The dispersion of severe COVID-19 has already occupied on pandemic extents, disturbing over 100 nations in a matter of months. A worldwide response to formulate health systems global is imperious. MATERIALS & METHODS: This is a cross sectional study conducted among the Saudi general public using an online survey. Saudis (male and female) of all ages willing to participate in this study were requested to fill up the survey. An online questionnaire was designed using Google Forms with questions related to personal and demographic information followed by COVID-10 related questions. RESULTS: A total of N=1026 subjects participated in this study and responded by completing the online survey. They were divided into groups including gender, age, education and profession type. As far as gender was concerned, 243 (23.7%) males and 783 (76.3%) females took part. CONCLUSION: Overall knowledge of Saudis regarding COVID-19 is above average.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".