Enclosure design for flock-level, chronic exposure of birds to air contaminant mixtures
Bibliographic record
Abstract
The objective of this study was to design an enclosure suitable for studying the ecotoxicological effects of vehicle emissions on groups of wild birds without compromising welfare. Two, adjacent enclosures sheltered from sunlight, wind and rain, were bird-proofed and wrapped with thick polyethylene sheeting. Emissions were directed into the treatment enclosure from the exhaust of a light-duty gasoline truck, using flexible, heat-proof pipe, with joins sealed to prevent leakage. During active exposure, the engine was idled for 5 h/day, 6 days/week for 4 weeks. Fans maintained positive pressure (controls) and negative pressure (treatment), preventing cross-contamination of enclosures and protecting investigators. Four sets of passive, badge-type samplers were distributed across each enclosure, measuring nitrogen dioxide, sulfur dioxide and volatile organic compounds (NO2, SO2 and VOCs, respectively), and were complemented by active monitors measuring VOCs and particulate matter (2.5 µm diameter, PM2.5). We found that the concentrations of NO2, SO2 and PM2.5 were not different between treatment and control enclosures. Volatile organic compounds (e.g. benzene, toluene, ethylbenzene and xylenes) were approximately six times higher in the treatment enclosure than control (13.23 and 2.13 µg m−1, respectively). In conclusion, this represents a successful, practical design for studying the effects of sub-chronic to chronic exposure to realistic mixtures of vehicle exhaust contaminants, in groups of birds. Recommended modifications for future research include a chassis dynamometer (vehicle treadmill), to better replicate driving conditions including acceleration and deceleration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| 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) | 0.000 | 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".