MEDECOR—A MEDICAL DECORPORATION TOOL TO ASSIST FIRST RESPONDERS, RECEIVERS, AND MEDICAL REACH-BACK PERSONNEL IN TRIAGE, TREATMENT, AND RISK ASSESSMENT AFTER INTERNALIZATION OF RADIONUCLIDES
Why this work is in the frame
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Bibliographic record
Abstract
After a radiological dispersal device (RDD) event, it is possible for radionuclides to enter the human body through inhalation, ingestion, and skin and wound absorption. From a health physics perspective, it is important to know the magnitude of the intake to perform dosimetric assessments. From a medical perspective, removal of radionuclides leading to dose aversion (hence risk reduction) is of high importance. The efficacy of medical decorporation strategies is extremely dependent upon the time of treatment delivery after intake. The "golden hour," or more realistically 3-4 h, is optimal when attempting to increase removal of radionuclides from extracellular fluids prior to cellular incorporation. To assist medical first response personnel in making timely decisions regarding appropriate treatment delivery modes, it is desirable to have a software tool that compiles existing radionuclide decorporation therapy data and allows a user to perform simple diagnosis leading to optimized decorporation treatment strategies. In its most simple application, the software is a large database of radionuclide decorporation strategies and treatments. The software can also be used in clinical interactive mode, in which the user inputs the radionuclide, estimated activity, route of intake and time since exposure. The software makes suggestions as to the urgency of treatment (i.e., triage) and the suggested therapy. Current developments include risk assessment which impacts the potential risk of delivered therapy and resource allocation of therapeutic agents. The software, developed for the Canadian Department of National Defence (DND), is titled MEDECOR (MEdical DECORporation). The MEDECOR tool was designed for use on both personal digital assistant and laptop computer environments. The tool was designed using HTML/Jscript, to allow for ease of portability amongst different computing platforms. This paper presents the features of MEDECOR, results of testing at a major NATO exercise, and future development of this tool into MEDECOR2.
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 | 0.001 |
| 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