Barcoding the<scp>C</scp>ollembola of<scp>C</scp>hurchill: a molecular taxonomic reassessment of species diversity in a sub‐<scp>A</scp>rctic area
Bibliographic record
Abstract
Although their functional importance in ecosystems is increasingly recognized, soil-dwelling micro-arthropods are usually poorly known in comparison with their above-ground counterparts. Collembola constitute a significant and species-rich component of the soil biodiversity, but it remains a woefully understudied group because of the taxonomic impediment. The ever-increasing use of molecular taxonomic tools, such as DNA barcoding, provides a possible solution. Here, we test the use of this approach through a diversity survey of Collembola from the vicinity of Churchill, Manitoba, Canada, and compare the results with previous surveys in the same area and in other sub-Arctic regions. The systematic barcoding campaign at Churchill revealed a diverse collembolan fauna consisting of 97 species-level MOTUs in six types of habitats. If all these MOTUs are confirmed as species, this richness would be far higher than prior records for Arctic Canada and could lead to reconsider the actual diversity of the group in Arctic environments.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".