Middle East Respiratory Syndrome Coronavirus Antibody Reactors Among Camels in Dubai, United Arab Emirates, in 2005
Bibliographic record
Abstract
We tested, using a low starting dilution, sequential serum samples from dromedary camels, sheep and horses collected in Dubai from February/April to October of 2005 and from dromedary camels for export/import testing between Canada and USA in 2000-2001. Using a standard Middle East respiratory syndrome coronavirus (MERS-CoV) neutralization test, serial sera from three sheep and three horses were all negative while sera from 9 of 11 dromedary camels from Dubai were positive for antibodies supported by similar results in a MERS-CoV recombinant partial spike protein antibody ELISA. The two negative Dubai camels were both dromedary calves and remained negative over the 5 months studied. The six dromedary samples from USA and Canada were negative in both tests. These results support the recent findings that infection with MERS-CoV or a closely related virus is not a new occurrence in camels in the Middle East. Therefore, interactions of MERS-CoV at the human-animal interface may have been ongoing for several, perhaps many, years and by inference, a widespread pandemic may be less likely unless significant evolution of the virus allow accelerated infection and spread potential in the human population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".