Background and persistence of fibers on vehicle seat belts
Bibliographic record
Abstract
Examination of the fibers transferred to vehicle seats and seat belts makes it possible to establish links in cases of vehicle theft or road accidents. Unlike seats, seat belts often have fibers that are fused to them owing to the significant forces encountered in the event of an accident, fibers that can be evaluated for their persistence and significant probative value. The aim of the project is to determine the background fiber population naturally present on seat belts, as well as to carry out simulations to study the persistence of the fibers. These were determined using zonal samples from seat belts of ten different vehicles. For the experiments, drivers of the vehicles had to wear a luminescent T-shirt for a total of 30 min, then remove it and continue driving normally for variable periods of time. The results show that the persistence of fibers on seat belts is heavily influenced by the number of times the driver fastened/unfastened their seat belt. The background population of fibers is comparable to the literature but can show important deviations when specific clothes are worn by the driver (i.e., winter accessories).
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".