Bibliographic record
Abstract
This thesis describes investigations that were carried out to determine the chemical compounds produced during the decomposition of an animal model in the absence of a soil matrix. In order to do this, several analytical methods were developed for various classes of compounds. Stillborn piglets and whole adult pig carcasses were used to model the decomposition process.Samples for analysis were collected from field trials conducted at decomposition research facilities in Perth and Canada. Two separate locations were used to provide a ‘compare and contrast’ approach to the identities of compounds detected following the analysis of decomposition fluid.Gas chromatography-mass spectrometry was used for preliminary studies into short chain fatty acids that have the potential to show reproducible patterns over certain postmortem intervals. Samples were analysed following a simple aqueous dilution and filtration. Additional compounds were detected, including several long chain fatty acids, which were also investigated for their potential as indicators of postmortem interval. Samples collected from the two separate locations, Western Australia (Perth) and Southern Canada (Oshawa) were analysed. This enabled a comparison of components to be carried out under significantly different climatic conditions. To verify the identity of the compounds, the predicted fragmentation patterns and possible mechanisms based on the library search results were also determined and compared with the obtained mass spectral traces from the fluid samples.A simple capillary zone electrophoresis method with detection by ultraviolet absorbance spectrophotometry was developed for the determination of biogenic amines and amino acids. Resolution and total analysis time was improved after the method was subject to optimisation utilising a chemometric approach. A screening design followed by a central composite design was carried out, with peak resolution and total analysis time as response factors. The optimised method was applied to porcine decomposition samples with target analytes identified by migration time and spiking. Samples were analysed following a 1:4 dilution with methanol, followed by filtration.A method utilising liquid chromatography-electrospray-mass spectrometry was employed for the determination of 23 amino acids and amines in decomposition fluid. The effect of a complex sample matrix was investigated and found to have little to no effect on the analyte signal. Decomposition fluid samples required no sample preparation, other than filtration. To avoid overloading the column, optimum sample injection volume was 0.1 μL. Compounds were identified through precursor → product ion transition(s). The specificity of the LC-ESI-MS system enabled identification of all target compounds as being present in decomposition fluid. The identity of compounds that showed apparent trends in decomposition fluid was verified by predicting possible mechanisms for the precursor → product ion transition(s).Analysis of data from each developed analytical method was conducted to establish any distinct relationship between the levels of particular compounds produced with respect to time and temperature. Preliminary results indicate that fatty acids show an 8-day cyclic trend, whilst total amino acid abundance shows a 14-day cyclic trend. Other compounds such as indole and putrescine showed general increasing trends over the course of the field trials.Several analytical methods to analyse target compounds in decomposition fluid have been presented in this thesis, however, suggestions for future work are presented in the final chapter.
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 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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".