IsoFresh: A global stable isotope database of freshwater food webs
Bibliographic record
Abstract
Ecologists seek to understand the ways that human activities are altering the structures and processes that support biodiversity and nature's contributions to people. Food web research at the interface of community and ecosystem ecology is promising in this regard. An industry of studies has utilized stable isotopes in recent decades to rapidly characterize energy and material transfer among organisms in freshwater food webs. Nevertheless, these efforts have been somewhat siloed and mainly locally-based, and lack of a centralized database has limited efforts to tackle questions about food web change using isotopes at a global scale. Here we present IsoFresh, a freshwater food web database that contains species-level carbon (δ13C) and nitrogen (δ15N) stable isotope values for 15343 organisms, representing 1001 food webs and including > 1600 fish species and associated potential prey, from 65 countries around the globe. Our hope is that IsoFresh is used to explore fundamental and applied food web questions, contributing new knowledge about global environmental change so that human societies can better conserve and manage freshwater ecosystems along desirable future trajectories.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".