The critical importance of experimentation in biomarker-based trophic ecology
Bibliographic record
Abstract
Fatty acids are commonly used as biomarkers for making inferences about trophic relationships in aquatic and soil food webs. However, researchers are often unaware of the physiological constraints within organisms on the trophic transfer and modification of dietary biomarkers in consumers. Fatty acids are bioactive molecules, which have diverse structures and functions that both complicate and enhance their value as trophic tracers. For instance, consumers may synthesize confounding non-dietary sourced markers from precursor molecules, and environmental conditions also affect fatty acid composition. There is a vital need for more research on the uptake and transfer of trophic biomarkers in individual organisms in order to advance the field and make meaningful use of these tools at the scale of populations or ecosystems. This special issue is focused on controlled feeding experiments on a diverse taxonomic breadth of model consumers from freshwater, marine and soil ecosystems with a goal of creating a more integrated understanding of the connection between consumer physiology and trophic ecology. This article is part of the theme issue 'The next horizons for lipids as 'trophic biomarkers': evidence and significance of consumer modification of dietary fatty acids'.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".