Using various lines of evidence to identify Chironomus species (Diptera: Chironomidae) in eastern Canadian lakes
Bibliographic record
Abstract
Chironomus Meigen (Diptera, Chironomidae) larvae are usually the largest sediment-burrowing chironomids, and as such often constitute a major part of the freshwater infaunal biomass. However, use of this genus in ecological, environmental and paleoecological studies is hampered by the fact that Chironomus larvae are difficult to identify to species because the larvae of many species are morphologically similar. We used a combination of morphological, cytological and genetic techniques to distinguish Chironomus larvae collected from 31 water bodies located in eastern Canada, producing 17 distinguishable groupings. These groups of larvae were ultimately identified as belonging to 14 known species (C. anthracinus, C. bifurcatus, C. cucini, C. decorus-group sp. 2, C. dilutus, C. entis, C. frommeri, C. harpi, C. maturus, C. nr. atroviridis (sp. 2i), C. ochreatus, C. plumosus, C. staegeri and C. 'tigris') and three other species that remain unidentified (C. sp. NAI-III). No single approach served to delimit and identify larvae of all 17 Chironomus species that we collected. Although we expected that morphological criteria alone would be insufficient, our results suggest that DNA barcoding, using either the mitochondrial cox1 or the nuclear gb2β gene, was also inadequate for separating some Chironomus species. Thus we suggest that multiple approaches will often be needed to correctly identify Chironomus larvae to species.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 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) | 0.001 | 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".