DNA entombed in archival seashells reveals low historical mitochondrial genetic diversity of endangered white abalone Haliotis sorenseni
Bibliographic record
Abstract
In this study we used decades-old shells of the endangered Northeast Pacific white abalone Haliotis sorenseni to produce high-quality DNA sequences for identification and historical diversity analysis. We obtained mitochondrial (mt) and nuclear DNA sequences (cytochrome c oxidase subunit I and histone H3 respectively) from shells with collection dates bracketing a period of population decline due to overexploitation, from throughout the species’ range. Illustrating the potential of shell DNA for forensic and conservation studies, we found two cases of misidentification among archival shell specimens. Diversity at the mitochondrial marker was lower in H. sorenseni throughout the 20th century than levels recently observed in two sympatric species that also suffered declines. The cause of comparatively low mtDNA diversity in white abalone is unclear; however, it cannot be exclusively linked to exploitation. DNA entombed in shells allowed us to directly establish historical genetic baselines for restoration of this endangered species. Vast repositories of shells exist in museum, aquaculture and private collections; the DNA contained within may be broadly investigated for studies of evolution, archaeology and conservation.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".