Environmental DNA detection of the male mitochondrial genome of freshwater mussels (Unionidae)
Bibliographic record
Abstract
Environmental DNA (eDNA) has shown promise for the detection of threatened and endangered species and has been implemented for monitoring aquatic spawning events. Freshwater unionid mussels exhibit a rare form of mitochondrial inheritance, in which males possess a unique mitochondrial mitotype that is divergent from the female mitotype. As freshwater mussels are spermcasters, the detection of male mitotype eDNA may provide critical conservation information related to timing of sperm release. This study re-purposed an existing eDNA metabarcoding dataset to detail the unique detection of eDNA pertaining to the male mitotype. Water samples collected alongside an extensive mussel salvage within the Walhonding River, Ohio, detected 16 distinct male mitotypes. However, several constraints limit the proper interpretation of these detections. There is currently a lack of reporting on assay compatibility with the male mitotype within freshwater mussel eDNA literature. Reference genetic databases are critically lacking, with only four of the 16 male eDNA sequences in this study able to be discerned to a species. This study highlights the importance of detailing these detections as the unique inheritance system provides opportunities to document difficult to record spawning behaviors, and eDNA may be employed as a survey tool to evaluate patterns of metapopulation geneflow.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".