Loop-mediated isothermal amplification for diagnosis of 18 World Organization for Animal Health (OIE) notifiable viral diseases of ruminants, swine and poultry
Bibliographic record
Abstract
Loop-mediated isothermal amplification (LAMP) is a simple, powerful state-of-the-art gene amplification technique used for the rapid diagnosis and early detection of microbial diseases. Many LAMP assays have been developed and validated for important epizootic diseases of livestock. We review the LAMP assays that have been developed for the detection of 18 viruses deemed notifiable of ruminants, swine and poultry by the World Organization for Animal Health (OIE). LAMP provides a fast (the assay often takes less than an hour), low cost, highly sensitive, highly specific and less laborious alternative to detect infectious disease agents. The LAMP procedure can be completed under isothermal conditions so thermocyclers are not needed. The ease of use of the LAMP assay allows adaptability to field conditions and works well in developing countries with resource-limited laboratories. However, this technology is still underutilized in the field of veterinary diagnostics despite its huge capabilities.
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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 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".