Exploring Applicability of Direct Analysis in Real Time with Mass Spectrometry (DART-MS) to Identify Homemade Explosive Residues Post-Blast
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
Application of Direct-Analysis-in-Real-Time (DART) ionization with mass spectrometry (DART-MS) to identify explosives from post-blast residues is presented. Explosives of interest represent real current threats encountered in criminal investigations in North America and Europe: homemade organic peroxides, binary explosives and smokeless powder. A series of simulated improvised explosive devices (IEDs) were manufactured using triacetone triperoxide (TATP), hexamethylene triperoxide diamine (HMTD), methyl ethyl ketone peroxide (MEKP), homemade binary explosives (composed of a fuel-oxidizer) and single and double-base smokeless powders. Each IED was configured to yield bomb fragments representative of actual materials recovered from bombing investigations. The goal of this study was to demonstrate the validity of DART-MS for identification of homemade explosives using real world samples (i.e. not laboratory simulations) and develop a quality assured method for use in accredited forensic laboratory settings.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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