UNESCO eDNA expedition in Socotra Archipelago (Yemen): June 2023
Bibliographic record
Abstract
This dataset contains the eDNA data collected as a part of the UNESCO eDNA expeditions in Marine World Heritage Sites project in 2022-2024. The project was coordinated in collaboration with the Ocean Biodiversity Information System (OBIS) of IOC-UNESCO and the marine programme of the UNESCO World Heritage Center, and funded by the government of Flanders (Kingdom of Belgium). The samples were collected with citizen science eDNA sampling kits, containing a syringe and a filter, and preserved with Longmire's buffer, before sequencing at a central laboratory. Five different biomarkers were analysed, including 12SMifish, Mimammal, Teleo, 16S-Vert and COI markers. The sequences were analysed with the PacMAN pipeline and quality controlled including a validation check by local scientists and site managers as well as compared to existing knowledge on species distributions in OBIS and GBIF. The full sampling protocols and materials are available on the project website (https://www.unesco.org/en/edna-training-materials?hub=66910), and the bioinformatics pipeline is on github (https://github.com/iobis/PacMAN-pipeline). The data can also be explored on the eDNA expeditions dashboard (https://dashboard.ednaexpeditions.org/).
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.007 |
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; both teacher heads agree on what is shown here.
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".