Isotopic applications assit in forensic tracking of illegally traded wildlife parts
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
Isotopic applications assit in forensic tracking of illegally traded wildlife parts Keith A. Hobson, a Research Scientist and Professor at Environment and Climate Change Canada, discusses the use of stable isotopes to trace the origins of animal parts in order to mitigate the illegal wildlife trade. As of 2022, the illegal global trade in tissues of (CITES and non-CITES listed) wildlife has been estimated to be on the order of $220 billion,(1) placing this practice among the top four of all global criminal enterprises. As ecosystems and the wild animals and plants they harbor come under increasing pressure from human developments, such trade threatens many species with decimation and ultimate extinction. Governments continue to struggle with the extent of this phenomenon and generally have few tools available to counter this growing trend. However, once seized, wildlife parts can be examined forensically to help ascertain provenance, and such tools can contribute in a small way to counter such criminal activity.
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 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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 it