Forensic Fibre Analysis by UV-Visible Microspectrophotometry
Bibliographic record
Abstract
This study evaluated various aspects of UV-VIS microspectrophotometry for routine colour analysis of fibres in a forensic laboratory, and was compared to visible microspectrophotometry. Quartz plates and glycerine mounting medium do not absorb within the spectral range of 240 nm to 380 nm. However, glass and XAM™ mounting medium, which are routinely used for microscopic fibre analysis and visible microspectrophotometry, were found to absorb substantially below 320 nm. The spectral interference from the polymeric composition of fibres was also studied. Wool, silk, polyester and acrylics with methylvinylpyridine(MVP) are highly absorbing below 310 nm, so dye colour analysis could not be applied in that region for these fibre types. Acetates, nylons, modacrylics and acrylics with polyvinylpyrrolidone (PVP) have low or moderate absorbance below 310 nm, which causes some interference. Cotton, rayon, and olefins do not absorb in the UV range. Analysis of glass-mounted fibres in the UV-VIS range can provide increased discrimination over analysis in the visible range. A flowchart decision tree was developed to guide the analyst in the application of UV-VIS microspectrophotometry for fibre analysis. Dyed fibres could initially be analysed under glass mount by UV-VIS microspectrophotometry from 320 nm to 770 nm. For fibre types with little or no polymeric UV spectral interference, additional spectral information could be obtained from UV-VIS analysis on quartz slides, measured from 240 nm to 770 nm.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 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".