Climate Change and Adolescent Health: An Evidence Gap Map Exercise
Bibliographic record
Abstract
eview question / Objective Research Questions -The research questions that will guide the evidence gap map exercise are as follows: 1.What are the documented impacts of climate change on adolescent health outcomes among adolescents aged 10-25 years? 2. How does climate change affect the risk of injury, lung disease, infectious disease, poor nutrition, sexual and reproductive health (SRH) issues, mental health, and education among adolescents?3. What are the socioeconomic implications of climate change on adolescent health?4. What interventions or strategies have been identified to mitigate the effects of climate change on adolescent health for adolescents aged 10-25 years?Background This evidence gap map exercise aims to examine climate change's impact on adolescent health, focusing on adolescents aged 10-19 years.The protocol outlines the research questions, population, search strategy, study designs, outcome measures, quality assessment, data synthesis, subgroup analysis, sensitivity analysis, and dissemination plans.Rationale The rationale for this evidence gap map exercise is to address the gaps in knowledge regarding the impact of climate change on adolescent health, specifically focusing on adolescents aged 10-19 years.Adolescence is a critical period of physical, cognitive, and psychosocial development, and climate change poses significant risks to their health, well-being, and prospects.Understanding the specific impacts and identifying evidence gaps will inform interventions and policies to protect adolescent health.
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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 | 0.049 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 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".