<p><strong>Checklist of oribatid mites (Acari: Oribatida) from two contrasting boreal fens: an update on oribatid mites of Canadian peatlands</strong></p>
Bibliographic record
Abstract
A checklist of the oribatid mite species from two boreal fens in Northern Ontario, Canada is presented. 174 peat soil samples, collected between 2015–2020, yielded a heterogeneous assemblage of 80 species, 57 genera and 33 families. Species richness and diversity were significantly higher in a Sphagnum-dominated fen (69 species) compared to a Carex-dominated fen (51 species), and although 40 species were found at both sites, overall composition was significantly different between the two sites. We also present an update to the seminal work of Behan-Pelletier and Bissett (1994) on Oribatida of Canadian peatlands with 45 new species records for peatlands. Records for the parthenogenetic families Brachychthoniidae Thor, 1934 and Suctobelbidae Jacot, 1938 were considerably expanded, but other families such as Punctoribatidae, Thor, 1937 remain poorly represented in Canadian peatlands. Taken together, species richness estimates range from 86–105 species based on our sampling and the number of undescribed species recorded suggests that the oribatid mite fauna still need further examination to encompass their actual biodiversity in peatlands. We report that the oribatid mite fauna of Canadian peatlands comprise 186 species that includes all published records as of February 2021 and species presented here.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".