X-rays have little impact on estimates of biodiversity from marine sedimentary ancient DNA metabarcoding
Bibliographic record
Abstract
Sedimentary ancient DNA (sedaDNA) recovered from marine sediments offers valuable insights into past ocean biodiversity through ecosystem reconstructions ranging from decadal to glacial-interglacial timescales. The current best-practice in ancient DNA research is to collect new sediment cores with clean sampling protocols in an effort to prevent modern DNA contamination and minimize post-collection DNA degradation. However, new core collection can pose a barrier to research due to the high costs associated with project-specific expeditions; it also excludes leveraging existing sediment core archives. In general, the recommendation is founded on an abundance of caution rather than evidence-based guidelines. Here, we present a comparative study on the impacts of X-Radiography sediment analysis and different extraction methods on marine sedaDNA outcomes in an archived core to help develop such guidelines. We found that exposure to standard X-ray imaging had no significant impact on sedaDNA recovery, co-extraction of inhibitors (e.g. humic acids), metabarcoding diversity metrics, community structure or composition. The extraction method, however, has a significant impact on sedaDNA recovery/inhibition, diversity metrics, community structure, and composition. Laboratory methodological design for marine sedaDNA studies is, therefore, a critical consideration for future research, whereas standard X-ray screening by marine geoscientists appears benign to the parameters measured. Our results support the use of archived sediments for prospective sedaDNA work, thus reducing a considerable barrier to the field.
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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".