Retrieval of hundreds of nuclear loci from herbarium specimens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Herbaria are unparalleled collections of biodiversity information representing the world's flora. However, this treasure has remained largely inaccessible to genetic studies, frequently limited by the low yields of poor‐quality DNA. Next‐generation sequencing (NGS) has transformed every field of biological research. The different strategies for accessing genetic data using NGS are changing the direction of biodiversity research—we are no longer constrained by a relatively small number of markers for non‐model organisms, by time and cost limited sample sizes, or by incomplete datasets due to recalcitrant DNA extractions or PCR amplification failure. Here we show that targeted enrichment through hybrid capture can be used to generate hundreds of kilobases of nuclear sequence data of the Neotropical genus Inga , from herbarium specimens as old as 180 years and using as little as 16 ng of degraded DNA.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it