ARISE project - Work package 3: Stable nitrogen isotopes of bulk tissue and amino-acids of ringed seals muscle and teeth's growth layer groups of harp seals from the Arctic and sub-Arctic
Bibliographic record
Abstract
This dataset includes stable nitrogen isotopes of bulk tissue (δ15Nbulk) and compound specific stable nitrogen isotopes on amino acids (δ15NAA) measured in harp seal (Pagophilus groenlandicus) teeth from Southern Barents Sea, Greenland Sea, Northwest Atlantic, and ringed seal (Pusa hispida) muscles from Canadian Arctic Archipelago and Baffin Island, in the Arctic and sub-Arctic. Teeth of harp seals from the Northwest Atlantic (n=48) were taken from archives in Fisheries and Oceans Canada (DFO) St John's, Canada from 1979 to 2016. Teeth of harp seals from the Barents Sea (n=72) and Greenland Sea (n=55) were taken from archives of the Institute of Marine Research (IMR), Norway, from 1963 to 2018 and 1953 to 2014, respectively. Muscle tissue from ringed seals were opportunistically sampled as part of Inuit subsistence harvests. Samples from the CAA were collected in Resolute from 1992 to 2016 (n=66). Muscle samples from the Baffin Bay were collected in Pangirtung from 1990 to 2016 (n=39). The seal samples were collected as part of Norwegian commercial sealing and student field courses from the University of Tromso in Norway (Barents Sea and Greenland Sea) and the Inuit subsistence and commercial harvests in Canada (Northwest Atlantic, Baffin Island, Canadian Archipelago). Analyses of δ15Nbulk and δ15NAA of seal tissue were carried out at the Liverpool Isotopes for Environmental Research laboratory, University of Liverpool. Results are reported here in standard δnotation (per mille) relative to atmospheric N2. This work resulted from the ARISE project (NE/P006035/1 and NE/P006310/1), as part of the Changing Arctic Ocean programme, funded by the UKRI Natural Environment Research Council (NERC).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.027 |
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".