Assessing diatom-mediated fatty acids in intertidal biofilm: a new conservation concern
Bibliographic record
Abstract
Abstract Biofilm communities on intertidal mudflats are recognized as major producers of nutrients, especially fatty acids. The rising threats posed by both climatic and anthropogenic stressors increase the necessity of understanding and conserving these communities. Shorebirds provide a proxy for studying the complex ecology of biofilm communities because of their heavy reliance on fatty acids from diatomaceous biofilm for successful long-distance migration. Herein, we review biofilm feeding patterns by migratory shorebirds, experimental design considerations for sampling and studying the fatty acid content of biofilm, and the literature describing established and emerging analytical methodology. Techniques for fatty acid analysis include the commonly employed gas chromatography–flame ionization detection (GC/FID) and gas chromatography–mass spectrometry (GC/MS) with derivatization. Liquid chromatography–mass spectrometry (LC/MS) and liquid chromatography–quadrupole time of flight (LC/QTOF) are newly emerging techniques that enable derivatization to be eliminated. In addition, Fourier transform infrared spectroscopy (FT/IR), a common instrument in chemistry laboratories, has applications in fatty acid research, specifically for screening. Using a combination of sampling and analytical methods is necessary for improved understanding of intertidal biofilm, both as a source of essential fatty acids in aquatic systems and a critical food for shorebirds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".