Development of a Draft Heavy Vehicle Rear Underride Guard Specification
Bibliographic record
Abstract
This paper summarizes results of a large research program intended to develop a draft rear underride guard specification for heavy vehicles. Results of a series of laboratory and full-scale crash tests performed at the Transport Canada Research Center were used in the development of these specifications. A total of eleven full-scale crash tests was carried out to evaluate the effectiveness of different underride guards. The first ten of these tests were performed on a simulated trailer attached guard. Four different underride guard designs were used in these ten full-scale crash tests. Three different vehicle models traveling at 48, 56 and 65 km/h speeds were used to impact underride guards head on. Results of the first ten crash tests show that the currently used US FMVSS 223 standard is far from adequate in preventing the occurrance of rear underride. Based on findings obtained from these crash tests, an improved guard design was developed and tested using a 16-meter trailer. This final crash test verified the effectiveness of improved guard design in reducing the undesirable effects of rear underride crashes. Based on the results, a draft heavy vehicle rear underride guard specification was developed.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".