Exploring human hair degradation: A preliminary study for estimating time-since-death
Bibliographic record
Abstract
Abstract Postmortem interval (PMI) estimation is a challenging task in forensic investigations. PMI assessment frequently requires the application of the currently available methods which can lead to unsatisfactory results due to the poor accuracy of time interval estimation. To address these concerns, the present study aimed to evaluate whether there is a correlation between human hair proteolysis and PMI. Scalp hair samples of three living donors and eleven individuals exhumed from different burial types from Portuguese cemeteries were analysed by ATR-FTIR (attenuated total reflectance – Fourier-transform infrared). Four band areas and three hair degradation indices were considered in the 2000–1000 cm −1 spectral region. When analysing the entire dataset (i.e., 126 infrared spectra) – and when separating and analysing the spectroscopic data by burial type – the ratio between amide II (∼1550 cm −1 ) and S = O and SO 3 combined (∼1074 cm −1 and ∼1043 cm −1 , respectively) suggests there is a correlation between hair proteolysis and PMI ( p < 0.05). Nevertheless, it is recommended that a larger dataset is required to confirm the preliminary results obtained in this study and to explore how this correlation can be used to estimate PMI in forensic casework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".