Ante- and post-mortem human volatiles for disaster search and rescue
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ante-mortem metabolic processes are responsible for the release of volatile organic compounds, which form the primary component of human scent and are used by search-and-rescue canines in victim location efforts. Similarly, the post-mortem processes of autolysis and putrefaction produce malodourous compounds that cadaver detection dogs use to locate human remains. This review examines literature on ante-mortem and post-mortem volatiles, with a focus on studies from 2010 onwards. A total of 973 different compounds were reported over this period, from the live matrices blood (65), breath (124), fingernails (17), hair (24), saliva (343), skin (385), sweat (37), urine (80), the whole body (86), and unspecified sources (31), and during early decomposition (321), middle decomposition (49), late decomposition (102), and an unspecified timeframe (113). There are notably more studies examining the matrices from living volunteers than decedents, and methods vary significantly between studies on living and deceased individuals in sampling methodology and analytical instrumentation. To establish a profile that accurately reflects the whole human volatilome, the standardisation of methodology and further research are required. Determining the complete human odour profile will assist in victim location where living and deceased individuals are commingled (e.g. disaster sites), and will inform future technologies to aid in accelerating search-and-rescue operations.
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.
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 | 0.000 | 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) | 0.000 | 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 it