Data on the diets of Salish Sea harbour seals from DNA metabarcoding
Bibliographic record
Abstract
Marine trophic ecology data are in high demand as natural resource agencies increasingly adopt ecosystem-based management strategies that account for complex species interactions. Harbour seal (Phoca vitulina) diet data are of particular interest because the species is an abundant predator in the northeast Pacific Ocean and Salish Sea ecosystem that consumes Pacific salmon (Oncorhynchus spp.). A multi-agency effort was therefore undertaken to produce harbour seal diet data on an ecosystem scale using, 1) a standardized set of scat collection and analysis methods, and 2) a newly developed DNA metabarcoding diet analysis technique designed to identify prey species and quantify their relative proportions in seal diets. The DNA-based dataset described herein contains records from 4,625 harbour seal scats representing 52 haulout sites, 7 years, 12 calendar months, and a total of 11,641 prey identifications. Prey morphological hard parts analyses were conducted alongside, resulting in corresponding hard parts data for 92% of the scat DNA samples. A custom-built prey DNA sequence database containing 201 species (192 fishes, 9 cephalopods) is also provided.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.007 | 0.038 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 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; 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".