Volatile organic compounds of diesel and porcine bone in a simulated controlled fire
Why this work is in the frame
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Bibliographic record
Abstract
The detection of burned human remains in a fire is daunting, mainly when identifiable skeletons are not found. This study aims to identify volatile organic compounds (VOC) released from the burning of porcine bones in the presence of diesel in a simulated controlled outdoor setting in Malaysia. Neat diesel was diluted with hexane with a ratio of 1:1 and administered into a gas chromatography-mass spectrometry (GC-MS). Porcine bone was burned to identify VOCs of porcine bones, whereas 30 mL diesel was burned together with porcine bones to identify VOCs produced from the combined burning. After the burning process, an activated carbon tablet was fixed to the burned sample. Later, the tablet was desorbed with hexane and analysed using GC-MS. Results revealed that the combined burning released a set of VOCs that were not detected in burned porcine bone or neat diesel. This work was able to enforce the detection of specific volatiles from various functional groups such as alkanes, isoalkanes, alkylbenzenes and ketones in the combined burning of diesel with porcine bones. It was also discovered that in the specific conditions applied and controlled in this study, most VOCs of porcine bone and diesel respectively were not detected in the combined burning of porcine bone and diesel.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| 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