Characterizing the Movement of Per- and Polyfluoroalkyl Substances in an Avian Aquatic–Terrestrial Food Web
Bibliographic record
Abstract
) in such systems may be exposed to PFAS from multiple abiotic and/or biotic compartments. We show from fatty acid signatures and carbon stable isotopes that tree swallow nestlings in southwestern Ontario fed on both terrestrial and aquatic macroinvertebrates. The PFAS profiles of air, terrestrial invertebrates, and swallows were dominated by perfluorooctanesulfonic acid (PFOS). Short-chain perfluoroalkyl acids (PFAAs) were largely restricted to air, surface water, and sediment, and long-chain PFAAs were mainly found in aquatic invertebrates and tree swallows. PFOS, multiple long-chain perfluorocarboxylic acids [perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluorotridecanoic acid (PFTrDA)] and perfluorooctane sulfonamide precursors were estimated to bioaccumulate from air to tree swallows. PFOS bioaccumulated from air to terrestrial invertebrates, and PFOS, PFDA, and perfluorooctane sulfonamidoacetic acids (FOSAAs) bioaccumulated from water to aquatic invertebrates. PFOS showed biomagnification from both terrestrial and aquatic invertebrates to tree swallows, and PFDA and FOSAAs were also biomagnified from aquatic invertebrates to tree swallows. The movement of PFAS through aquatic-terrestrial food webs appears congener- and compartment-specific, challenging the understanding of PFAS exposure routes for multiple species involved in these food webs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".