Using the rDNA Internal Transcribed Spacer 1 to Identify the Invasive Pest<i>Rhagoletis cerasi</i>(Diptera: Tephritidae) in North America
Bibliographic record
Abstract
The cherry-infesting fruit fly Rhagoletis cerasi Loew is a significant commercial pest in Europe that has recently invaded North America. To date, it has been trapped only in Canada and northwestern counties of New York. It has the potential to spread further and threaten production and movement of cherry commodities. Timely diagnosis of the pest will facilitate surveys and quick response to new detections. Adult morphology of the pest is distinct from other flies in North America. However, when flies are significantly damaged on traps or the immature life stages are found in fruits, molecular methods of identification are important to confirm presence and host-use records. Other than DNA sequencing of genes from flies which takes over a day to complete, there are no timely methods of molecular identification for this pest. In this study, we report the first sequence record of the internal transcribed spacer 1 (ITS1) from R. cerasi and develop two diagnostic tests for the pest based on ITS1 differences among species in North America. The tests use loop-mediated isothermal amplification (LAMP) and multiplex, conventional polymerase chain reaction (mcPCR) technologies that target the same region of the R. cerasi ITS1 sequence. Both tests performed well when tested against collections of R. cerasi from North America and Europe, generating Diagnostic Sensitivity estimates of 98.4-99.5%. Likewise, the tests had relatively high estimates of Diagnostic Specificity (97.8-100%) when tested against Rhagoletis Loew species present in North America that also use cherry as a developmental host.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".