A meta-collection of nitrogen stable isotope data measured in Arctic marine organisms from the Canadian Beaufort Sea, 1983–2013
Bibliographic record
Abstract
Abstract Objectives Existing information on Arctic marine food web structure is fragmented. Integrating data across research programs is an important strategy for building a baseline understanding of food web structure and function in many Arctic regions. Naturally-occurring stable isotope ratios of nitrogen (δ15N) and carbon (δ13C) measured directly in the tissues of organisms are a commonly-employed method for estimating food web structure. The objective of the current dataset was to synthesize disparate δ15N, and secondarily δ13C, data in the Canadian Beaufort continental shelf region relevant to trophic and ecological studies at the local and pan-Arctic scales. Data description The dataset presented here contains nitrogen and carbon stable isotope ratios (δ15N, δ13C) measured in marine organisms from the Canadian Beaufort continental shelf region between 1983 and 2013, gathered from 27 published and unpublished sources with associated sampling metadata. A total of 1077 entries were collected, summarizing 8859 individual organisms/samples representing 333 taxa across the Arctic food web, from top marine mammal predators to primary producers.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.031 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".