[WEARING A MASK IS A PERSONAL PROTECTION AGAINST SARS-COV-2 INFECTION EVEN IN A VACCINATION-ON-BOARDING COUNTRY].
Bibliographic record
Abstract
INTRODUCTION: Even with the advent of the COVID-19 vaccine, masks and social distancing are recommended as a precautionary measure to suppress SARS-CoV-2 infection and disease. In Israel, as in many other countries, despite official regulations and widespread availability and accessibility to affordable effective masks, the use of face masks is not consistent or universal. Physicians and other medical and health professionals have a vital role to play in communicating to the public about the importance of masking and encouraging people to wear face masks correctly and consistently. This review underscores the importance of masking as a protective public health mitigation measure. It describes types of face masks mainly used by the public and their effectiveness. It emphasizes the importance of identifying and addressing barriers (e.g., physical, social, economic) to encourage widespread and sustained appropriate use of masks. The article also proposes strategies to enhance masking, such as changing social norms through targeted local interventions and governmental control of mask quality and price.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".