Combined hardware--software considerations for triage of internally contaminated personnel
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
Medical response to a radiological emergency involves first assessing, triaging and treating trauma, followed by determining potential hazard from radiological intake. A combined hardware-software strategy is required for this mission. The hardware strategy should consist of a dedicated detector suite capable of alpha, beta and gamma radiation detection, identification and quantification suitable for order of magnitude dose assessment. The hardware platform should provide a simple user interface suitable for field deployment. The software should provide first-on-the-scene responders with the ability to perform radiological triage in a mass casualty type event, physicians with the ability to assign treatment regimes, and long-term care medical personnel with information to provide continual risk reassessment of the patient taking into account toxicology of the decorporation therapy and dose aversion. The software should be rich in data, yet accessible through a simple user interface. Practicing in a radiological emergency exercise environment with the equipment is crucial to its efficacy in a real emergency.
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 | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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