Development of a Polymerase Chain Reaction Lateral Flow Immunoassay for Rapid Authentication of Venison in Food Products
Bibliographic record
Abstract
Abstract A novel polymerase chain reaction lateral flow immunoassay (PCR-LFI) test was developed to detect venison in food products in a rapid, inexpensive, and user-friendly manner. The LFI strips allowed the detection of PCR products within 5 min by reading the color signals with the naked eye. The PCR-LFI test uncovered a high specificity for venison with no cross-reactivity to 19 animal and plant species and enabled the detection of raw, oven-heated, and fried venison in binary mixtures with a limit of detection (LOD) of 0.01% (w/w), which was lower than the LOD of PCR agarose gel electrophoresis [0.1% (w/w)]. In addition, the PCR-LFI test was applied to detect 15 commercial venison products, and the results were validated by PCR agarose gel electrophoresis. Given its superiority in terms of cost, reliability, and simplicity, the PCR-LFI test has great potential to be employed as a meat authentication tool in the food industry.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".