The International Vertebrate Pet Trade Network and Insights from US Imports of Exotic Pets
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
The international trade in exotic vertebrate pets provides key social and economic benefits but also drives associated ecological, ethical, and human health impacts. However, despite its clear importance, we currently lack a full understanding of the structure of the pet trade, hampering efforts to optimize its benefits while mitigating its negative effects. In the present article, we represent and review the structure of the pet trade as a network composed of different market actors (nodes) and trade flows (links). We identify key data gaps in this network that, if filled, would enable network analyses to pinpoint targets for management. As a case study of how data-informed networks can realize this goal, we quantified spatial and temporal patterns in pets imported to the United States. Our framework and case study illustrate how network approaches can help to inform and manage the effects of the growing demand for exotic pets.
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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