Effect of Substrate Interferences from High‐Density Polyethylene on Association of Simulated Ignitable Liquid Residues with the Corresponding Liquid
Bibliographic record
Abstract
The effect of substrate interferences from high-density polyethylene (HDPE) on the ability to associate an ignitable liquid residue with the corresponding liquid standard, using statistical procedures, is demonstrated. Gasoline, kerosene, and lighter fluid, at three different evaporation levels, were spiked onto HDPE and subsequently burned to generate simulated ignitable liquid residues (ILRs). Samples were extracted using a passive headspace procedure and analyzed by gas chromatography-mass spectrometry. The total ion chromatograms were subjected to data pretreatment procedures prior to principal components analysis and Pearson product moment correlation. Using the combination of these statistical procedures, simulated ILRs were successfully associated with the corresponding liquid type, despite the presence of compounds inherent to the HDPE substrate, as well as those resulting from pyrolysis of the substrate.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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 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".