Mink, SARS-CoV-2, and the Human-Animal Interface
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
Mink are small carnivores of the Mustelidae family. The American mink is the most common and was imported to Europe, Asia, and Latin America for breeding, as its fur is very popular. Denmark, the Netherlands, and China are the biggest producers of mink. Mink farms with a high population density in very small areas and a low level of genetic heterogeneity are places conducive to contagion. The mink's receptor for SARS-CoV-2 is very similar to that of humans. Experimental models have shown the susceptibility of the ferret, another mustelid, to become infected with SARS-CoV-2 and to transmit it to other ferrets. On April 23, 2020, for the first time, an outbreak of SARS-CoV-2 in a mink farm was reported in the Netherlands. Since then, COVID-19 has reached numerous mink farms in the Netherlands, Denmark, United States, France, Greece, Italy, Spain, Sweden, Poland, Lithuania, and Canada. Not only do mink become infected from each other, but also they are capable of infecting humans, including with virus variants that have mutated in mink. Human infection with variant mink viruses with spike mutations led to the culling in Denmark of all mink in the country. Several animals can be infected with SARS-CoV-2. However, anthropo-zoonotic outbreaks have only been reported in mink farms. The rapid spread of SARS-CoV-2 in mink farms raises questions regarding their potential role at the onset of the pandemic and the impact of mutants on viral fitness, contagiousness, pathogenicity, re-infections with different mutants, immunotherapy, and vaccine efficacy.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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