The Use of Fiber-Reinforced Polymers in Wildlife Crossing Infrastructure
Bibliographic record
Abstract
The proven effectiveness of highway crossing infrastructure to mitigate wildlife-vehicle collisions with large animals has made it a preferred method for increasing motorist and animal safety along road networks around the world. The crossing structures also provide safe passage for small- and medium-sized wildlife. Current methods to build these structures use concrete and steel, which often result in high costs due to the long duration of construction and the heavy machinery required to assemble the materials. Recently, engineers and architects are finding new applications of fiber-reinforced polymer (FRP) composites, due to their high strength-to-weight ratio and low life-cycle costs. This material is better suited to withstand environmental elements and the static and dynamic loads required of wildlife infrastructure. Although carbon and glass fibers along with new synthetic resins are most commonly used, current research suggests an increasing incorporation and use of bio-based and recycled materials. Since FRP bridges are corrosion resistant and hold their structural properties over time, owners of the bridge can benefit by reducing costly and time-consuming maintenance over its lifetime. Adapting FRP bridges for use as wildlife crossing structures can contribute to the long-term goals of improving motorist and passenger safety, conserving wildlife and increasing cost efficiency, while at the same time reducing plastics in landfills.
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 | 0.000 | 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 | 0.000 | 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 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".