Stable isotope ratio and elemental contents for salmon muscle tissue collected from the F/V Northwest Explorer during the 2022 International Year of the Salmon Pan-Pacific Winter High Seas Expedition
Bibliographic record
Abstract
North Pacific salmon (Oncorhynchus spp.) were caught by deploying trawl nets in April (4-18) 2022 during the winter expeditions of the International Year of the Salmon to the North Pacific high seas onboard the F/V Northwest Explorer. Trawl nets were deployed at each station in the top 50 meters of the water column and towed for 60 minutes (night) or 90 minutes (day) at 4 to 5 knots. A 2x2 cm sample of salmon muscle tissue was collected from above the lateral line and in front of the dorsal fin and stored at -80°C. Muscle samples were then processed in the laboratory at the University of British Columbia. Tissue was lyophilized in freeze drier for 48 hours, homogenized using mortar and pestle, encapsulated in tin (Sn) capsules, and sent for measurements of carbon and nitrogen stable isotope ratios and elemental contents at an external lab. Samples were analysed on an Elemental Analyser coupled to an Isotope Ratio Mass Spectrometer. Details on analytical procedure are provided in the supplementary materials 1 and 2. The data reported includes each sample ẟ13C, %C, ẟ15N, % N, and CN ratios, in addition to the metadata associated with each sample (e.g., coordinates of oceanographic station and bottom depth where salmon specimen was collected, etc.).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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".