A validated targeted assay for environmental DNA detections of the Atlantic wolffish (Anarhichas lupus)
Bibliographic record
Abstract
Abstract The Atlantic wolffish (Anarhichas lupus) was assessed as a species of Special Concern by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) under the Canadian Species-At-Risk Act (SARA) in 2001, and by the National Marine Fisheries Service in USA in 2004. Monitoring of marine Species-At-Risk would rely ideally on non-destructive methods. However, most monitoring of marine fish at-risk rely on trawl surveys that are potentially destructive of the environment. Inferring a species presence using environmental DNA (eDNA) detections offers an attractive alternative for Species-At-Risk monitoring, because it is non-destructive, specific, and sensitive. We developed and optimized a real-time quantitative PCR probe-based (qPCR) detection protocol that targets the eDNA of Atlantic wolffish,A. lupus. The qPCR protocol was validatedin silico,in vitro, andin situ. Species-specificity was assessedin vitroby testing against the two other species ofAnarhichaspresent in the northwest Atlantic. We did not observe DNA amplification for either of these two species. The assay was highly sensitive, with a limit of detection (95% confidence level) of 1.5 DNA copies per qPCR reaction.In situtests showed thatA. lupuseDNA is detected from expected depth strata in areas of known wolffish abundance. This study provides a proof-of-concept experiment that offers a robust, targeted, and non destructive protocol for detection eDNA of the Atlantic wolffish.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".