Evaluating the use of coded-wire tags in individually marking Odonata larvae
Bibliographic record
Abstract
Abstract We tested a potential new tool for marking Odonata larvae internally, evaluating the retention rates of injected coded-wire tags (CWT) and the effects of these tags on larval performance. Two species of dragonfly larvae (Epitheca canis McLachlan (Odonata: Corduliidae) and Leucorrhinia intacta Hagen (Odonata: Libellulidae)) were injected with CWT. Tag loss rates were assayed over experimental periods of 22 and 60 days, respectively for the two species. To assess whether tagging had negative effects on larvae, mortality, and growth of tagged larvae were compared to untagged larvae held in the same conditions. Tag retention rates were high (92–100%) and CWT were easily retrieved from preserved larvae via dissection, permitting most tagged larvae to be individually identified. There was 100% survival in larvae injected with CWT and tags do not appear to impair growth. The high retention and retrieval rates of this marking approach combined with no increase in mortality associated with tagging suggest that CWT are a useful means of individually labelling a large number of Odonata larvae in a time-efficient manner.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".