DNA barcoding facilitates associations and diagnoses for Trichoptera larvae of the Churchill (Manitoba, Canada) area
Bibliographic record
Abstract
BACKGROUND: The North American Trichoptera larvae are poorly known at the species level, despite their importance in the understanding of freshwater fauna and critical use in biomonitoring. This study focused on morphological diagnoses for larvae occurring in the Churchill, Manitoba area, representing the largest larval association effort for the caddisflies at any given locality thus far. The current DNA barcode reference library of Trichoptera (available on the Barcode of Life Data Systems) was utilized to provide larval-adult associations. RESULTS: The present study collected an additional 23 new species records for the Churchill area, increasing the total Trichoptera richness to 91 species. We were able to associate 62 larval taxa, comprising 68.1% of the Churchill area Trichoptera taxa. This endeavor to identify immature life stage for the caddisflies enabled the development of morphological diagnoses, production of photographs and an appropriate taxonomic key to facilitate larval species analyses in the area. CONCLUSIONS: The use of DNA for associations of unknown larvae with known adults proved rapid and successful. This method should accelerate the state-of-knowledge for North American Trichoptera larvae as well as other taxonomic lineages. The morphological analysis should be useful for determination of material from the Churchill area.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".