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Record W6907610636 · doi:10.21966/j6kt-9p56

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

2022· dataset· en· W6907610636 on OpenAlexaff

Bibliographic record

VenueHakai Institute · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMuscle tissueStable isotope ratioIsotope analysisAnalyserWater columnWet weightIsotopeδ15N

Abstract

fetched live from OpenAlex

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.).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.020
GPT teacher head0.246
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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