The sample was restricted to sedentary adults from an educational setting, limiting generalizability to diverse populations across different contexts.
Research gap analysis derived from 3 computer_science papers in our local library.
The gap
The sample was restricted to sedentary adults from an educational setting, limiting generalizability to diverse populations across different contexts.
Consensus across the literature
Clustered from 3 gap mentions across 3 papers via embedding cosine ≥ 0.62.
Research trend
Established — well-defined area with open sub-problems.
Supporting evidence — 3 representative gaps
- Deep learning characterizes depression and suicidal ideation in young adults from eye movements (2026) · doi
The study was limited to young adults (18-25 years old) recruited from a single city (Los Angeles), leaving open questions about generalizability to other age groups and geographic populations.
Keywords: limited young adults years recruited single city angeles leaving open questions generalizability groups geographic populations - Smartwatch-Based Multidimensional Training Program to Improve Holistic Health Outcomes in Sedentary Adults (2026) · doi
The sample was restricted to sedentary adults from an educational setting, limiting generalizability to diverse populations across different contexts.
Keywords: sample restricted sedentary adults educational setting limiting generalizability diverse populations across different contexts - Hospital Triage Optimization: Evaluation of Machine Learning Models for Blood Pressure Estimation to Enhance Emergency Response in Colombia (2026) · doi
The study's applicability is limited to isolated regions with specific demographic and comorbidity characteristics; generalization to other populations requires validation.
Keywords: applicability limited isolated regions specific demographic comorbidity characteristics generalization populations requires validation
Explore this gap further
Search “The sample was restricted to sedentary adults from an educational setting, limiting generalizability to diverse populations across different contexts.” across open scholarly engines for the latest related literature.
Working on this gap? Publish with us.
Science AI Journal reviews manuscripts in under 15 minutes with 8 specialised AI reviewers calibrated on 23,000+ real peer reviews. Open access, CC BY 4.0.
Free tools for your next paper
Related gaps in Computer Science
- Finally, we identify gaps in the knowledge of sex differences in athletic performance and the underlying mechanisms, providing substantial opportunities for high-impact studies.Finally, we identify gaps in the knowledge of sex differences in athletic performance and the underlying mechanisms, providing substantial o…
- For verbal working memory, these near-transfer effects were not sustained at follow-up, whereas for visuospatial working memory, limited evidence suggested that such effects might be maintained.For verbal working memory, these near-transfer effects were not sustained at follow-up, whereas for visuospatial working memory, limited evi…
- Although large language models often produce impressive outputs, it remains unclear how they perform in real-world scenarios requiring strong reasoning skills and expert domain knowledge.Although large language models often produce impressive outputs, it remains unclear how they perform in real-world scenarios requiring stron…
- In deep learning (DL), the deep generative model is helpful for data augmentation objectives to tackle the lack of datasets that have a significant impact on learning performance.In deep learning (DL), the deep generative model is helpful for data augmentation objectives to tackle the lack of datasets that have a sign…