Perspective: Integration to Implementation (I-to-I) and the Micronutrient Forum—Addressing the Safety and Effectiveness of Vitamin A Supplementation
Bibliographic record
Abstract
An ongoing challenge to our ability to address the role of food and nutrition in health promotion and disease prevention is how to design and implement context-specific interventions and guidance that are safe, efficacious, and avoid unintended consequences. The integration to effective implementation (I-to-I) concept is intended to address the complexities of the global health context through engagement of the continuum of stakeholders involved in the generation, translation, and implementation of evidence to public health guidance/programs. The I-to-I approach was developed under the auspices of the Micronutrient Forum and has been previously applied to the question of safety and effectiveness of interventions to prevent and treat nutritional iron deficiency. The present article applies the I-to-I approach to questions regarding the safety and utility of large-dose vitamin A supplementation programs, and presents the authors' perspective on key aspects of the topic, including coverage of the basic and applied biology of vitamin A nutrition and assessment, clinical implications, and an overview of the extant data with regard to both the justification for and utility of available intervention strategies. The article includes some practical considerations based on specific country experiences regarding the challenges of implementing vitamin A-related programs. This is followed by an overview of some challenges associated with engagement of the enabling communities that play a critical role in the implementation of these types of public health interventions. The article concludes with suggestions for potential approaches to move this important agenda forward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.053 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.041 |
| Scholarly communication | 0.024 | 0.020 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.033 | 0.036 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".