Determining Polycyclic Aromatic Compounds in Bird Feathers Using Pressurized Fluid Extraction
Bibliographic record
Abstract
Due to their ease of collecting and transporting from the field and their ability to accumulate pollutants, bird feathers are increasingly being used as a non-invasive biomonitoring tool for environmental monitoring programs. Polycyclic aromatic compounds (PACs) are a diverse class of environmental pollutants, and because of their deleterious impacts on biological species, monitoring these compounds in wildlife is of high importance. Current approaches to measuring PACs in bird feathers involve a time-consuming acid treatment with a concomitant solvent extraction step. Here, a validated method for measuring a suite of PACs in bird feathers using pressurized fluid extraction and identification and quantitation by gas chromatography-tandem mass spectrometry is presented. Chicken (Gallus domesticus) feathers were purposely fortified with a suite of 34 PACs separately at three fortification levels and placed inside a pressurized fluid extraction cell containing silica gel/deactivated alumina to provide in situ clean-up of the sample. Except for anthracene and naphthalene, the accuracy of our method ranged for PAHs from 70–120% (irrespective of fortification level), and our intra- and inter-day repeatability was smaller than 28%. For APAHs, our accuracies ranged from 38–158%, and the inter- and intra-day repeatability was less than 35%. Our limits of detection and quantitation for both groups of compounds ranged from 0.5–13 and 1.5–44.3 ng/g, respectively. Overall, the developed method represents an effective and efficient approach for the extraction and quantitation of PACs from bird feathers that negated the need for the time-consuming and potentially harmful acid treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".