A Workshop on Cognitive Aging and Impairment in the 9/11-Exposed Population
Bibliographic record
Abstract
The terrorist attacks on 11 September 2001 potentially exposed more than 400,000 responders, workers, and residents to psychological and physical stressors, and numerous hazardous pollutants. In 2011, the World Trade Center Health Program (WTCHP) was mandated to monitor and treat persons with 9/11-related adverse health conditions and conduct research on physical and mental health conditions related to the attacks. Emerging evidence suggests that persons exposed to 9/11 may be at increased risk of developing mild cognitive impairment. To investigate further, the WTCHP convened a scientific workshop that examined the natural history of cognitive aging and impairment, biomarkers in the pathway of neurodegenerative diseases, the neuropathological changes associated with hazardous exposures, and the evidence of cognitive decline and impairment in the 9/11-exposed population. Invited participants included scientists actively involved in health-effects research of 9/11-exposed persons and other at-risk populations. Attendees shared relevant research results from their respective programs and discussed several options for enhancements to research and surveillance activities, including the development of a multi-institutional collaborative research network. The goal of this report is to outline the meeting's agenda and provide an overview of the presentation materials and group discussion.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".