Publicly-shared DNA barcodes and citizen science images provide new evidence on the establishment and spread of a lantana biological control agent, <i>Orphanostigma haemorrhoidalis</i> (Lepidoptera, Crambidae)
Bibliographic record
Abstract
Abstract Orphanostigma haemorrhoidalis (Guenée) (Lepidoptera, Crambidae), indigenous to the Americas, was widely used in the Old World for the biological control of Lantana camara L. (Verbenaceae) from the 1950s to the 1980s. DNA barcodes from the Barcode of Life Data System (BOLD) and citizen scientist images from the iNaturalist and Afromoths websites were used to detect the establishment and spread of O . haemorrhoidalis in countries where it has not previously been reported. Analysis of DNA barcodes showed that there are two genetically distinguishable populations of O . haemorrhoidalis in the Americas, one in the south-eastern USA and the other widespread in the rest of the Neotropics. The two populations were introduced into different parts of the World and subsequently spread. We used DNA barcodes from BOLD to clarify that a population from Florida is established in Hawai’i, Australia and Fiji, while a population from Trinidad is established in parts of mainland Africa (including new records for Cameroon, Nigeria and Ghana), Madagascar, Mauritius and La Réunion. New country records for O . haemorrhoidalis were established from iNaturalist images from Eswatini, Kenya and Mozambique, and from Afromoths for Tanzania.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".