Electrophysiological responses of Chrysomya rufifacies (Diptera: Calliphoridae) to active volatile organic compounds released by human and pig decomposition
Bibliographic record
Abstract
Forensic entomology is an important discipline which utilizes the developmental and behavioural patterns of insects which colonize decomposing tissue in a medicolegal context, most commonly to determine the post-mortem interval (PMI). Chryosmya rufifacies (Macquart) (Diptera: Calliphoridae) is a secondary colonizer of human decomposition in North America and its predatory behaviour can affect successional data, and therefore alter PMI estimations. Determining the specific volatile organic compounds which induce a response in C. rufifacies could mitigate the effects of this predatory species by providing empirical indications of the behaviourally active compounds released by decomposition. The specific compounds which cause a response in this species were isolated and identified via GC-MS, electroantennography (EAG) and GC-EAG. Electrophysiologically active volatile organic compounds (VOCs) derived from human and pig decomposition were analysed and compared, indicating that pigs are an acceptable human analogue. Six EAG-active compounds were identified via coupled GC-EAG of the VOC samples; BAME, DMDS, DMTS, ethanol, indole and phenol. Dose response testing was conducted, confirming DMTS and BAME as EAG-active compounds. Ethanol was determined to not be EAG-active in C. rufifacies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".