PCR-Based Amplification of a Cox1 Mini-DNA Barcode Gene from Feces: A Non-Invasive Molecular Technique to Identify Environmental DNA Samples of Maritime Shrew (Sorex maritimensis)
Bibliographic record
Abstract
Sorex maritimensis (Maritime Shrew) is endemic to Canada and found only in Nova Scotia and New Brunswick. The Maritime Shrew has been identified as one of the vertebrate species in Nova Scotia that is most susceptible to the effects of climate change and global warming, and it is listed by NatureServe as vulnerable (category G3). While generally regarded as a wetland specialist, relatively little is known about its specific habitat preferences. Non-invasive methods of sampling have proven valuable in identifying and monitoring such rare species. The objective of this study was to optimize a non-invasive method to document presence of Maritime Shrews using collected fecal DNA and to develop a PCR-based protocol to amplify a short, ∼120 base-pair section of the cox1 gene using shrew-specific primers. We used baited feeding tubes to collect shrew feces. We designed cox1 PCR primers to preferentially amplify this mini-DNA barcode for shrews in samples that may contain feces from rodents as well. We designed the primers to amplify a small amplicon to increase the likelihood of successful amplification from degraded DNA. This technique is likely to be effective for documenting the distribution and habitat preferences of this relatively rare shrew in Nova Scotia and New Brunswick.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".