Quantified Explosives Transfer on Surfaces for the Evaluation of Trace Detection Equipment
Bibliographic record
Abstract
Trace explosive test surfaces are often required for the evaluation of trace detection equipment to determine the equipment performance. Test surfaces of C-4, Detasheet, Semtex-H, TNT, and HMTD were prepared by transferring trace amount of explosive deposited on polytetrafluoroethylene (PTFE) transfer strips onto different surfaces (Kraft paper, hard plastic, woven fabric, and soft vinyl). The amount of explosive transferred was deduced from the amount of explosive remaining on the PTFE strips after transfer, as quantified by direct analysis using tandem mass spectrometry with thermal desorption. From the data set of over 2000 transfers, we experienced lower transfer efficiency for Semtex-H and Detasheet, and for soft vinyl and hard plastic. However, the rapid quantification mass spectrometric method allowed the transfer efficiency to be determined for all test surfaces used in an evaluation of trace explosive detectors, thereby permitting only the test surfaces with desired transfer to be accepted for the assessment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".