Contrast sensitivity and visual hallucinations in patients referred to a low vision rehabilitation clinic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<h3>Objective</h3> Mental health problems are prevalent in youth with rheumatologic disease. Gaps in knowledge exist regarding their effect, as well as strategies for detection and effective treatment. To address these gaps, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Mental Health Workgroup developed and prioritized an agenda of research topics. <h3>Methods</h3> We systematically reviewed the literature and identified 5 major research domains in further need of study: (A) mental health burden and relationship to pediatric rheumatologic disease, (B) effect of mental health disorders on outcomes, (C) mental health awareness and education, (D) mental health screening, and (E) mental health treatment. Research topics within these areas were developed by workgroup leaders and refined by the workgroup. Members were surveyed to prioritize the topics by importance, feasibility of study, and actionability. <h3>Results</h3> Fifty-nine members (57%) completed the survey. Among the proposed research topics, 31/33 were rated as highly important and 4/33 were rated highly for importance, feasibility, and actionability. Topics rated most important related to (A) mental health burden and relationship to rheumatologic disease, and (B) the effect of mental health on outcomes. Topics rated most feasible and actionable were related to (D) mental health screening. <h3>Conclusion</h3> Addressing gaps in knowledge regarding mental health in youth with rheumatologic disease is essential for improving care. We have identified high priority research topics regarding mental health of pediatric rheumatology patients in need of further investigation that are feasible to study and believed to lead to actionable results in patient care.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it