Distribution and abundance of baling twine in the landscape near Osprey (<em>Pandion haliaetus</em>) nests: implications for nestling entanglement
Bibliographic record
Abstract
Polypropylene baling twine used by Ospreys (Pandion haliaetus) during nest construction creates a risk of entanglement for nestlings and adults on the yellowstone River, Montana. In 2013, we evaluated the abundance of twine in 2-km-radius buffer zones centred on 38 nests for three categories of road density. We found more twine per kilometre along roads in low (n = 19) and moderate (n = 13) road density nest buffer zones than in high road density nest buffer zones (n = 6). The estimated total amount of twine found along roads in nest buffer zones ranged from 0 to 2602 m and did not differ among road density strata. The percentage of Osprey nests containing twine was highest in low (63.2%) and moderate (61.5%) road density nest buffer zones and lowest (33.3%) in high road density buffer zones, which reflected a gradient from rural and suburban to urban landscapes. The estimated total amount of twine within a nest buffer zone did not predict whether a nest contained twine. The amount of twine found in seven nests destroyed by wind or power company personnel ranged from 0 to 206 m and was not correlated with the amount of twine found in their buffer zones. During the 2012 and 2013 breeding seasons, four of 120 nestlings (3.3%) became entangled in twine: two were cut free and fledged normally, one died, and one was euthanized. The abundance of twine in the environment surrounding nests and its slow rate of biodegradation mean that vigilance by citizen scientist nest monitors and assistance from power companies are the only short-term solution to reducing mortality resulting from entanglement.
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 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".