Minimizing the Risk of Lap/Shoulder Belted Children Submarining the Lap Belt in Frontal Crashes
Bibliographic record
Abstract
The objective of the study presented by this paper was to determine whether belt-positioning-booster (BPB) seats incorporate seat bottom design features, identified by previous research, to minimize the risk of submarining. The booster seats were evaluated through inspection and testing. The geometry of the BPB’s seat bottom was measured and recorded. The comparative restraining ability of the BPB’s seat bottom ramp was tested. The compressibility of the BPB while seated on a vehicle seat was tested. The compressibility of the BPB alone was also tested using the test specified in the Canadian and Australian/New Zealand standards. The inspection and load testing of various BPBs, as reported in this paper, reveals that BPB seat bottom designs vary significantly. Some BPBs incorporate significant seat ramp geometry and have very little compressibility. Others have no seat ramp at all and have very high compressibility. It is critical that BPB manufacturers understand the importance of anti- submarining seat bottom ramps and low compressibility of the seating surface, and incorporate these features into all BPBs. To ensure this and do so in a manner that is consistently compatible with vehicle seats and seat belts, the authors recommend that National Highway Traffic Safety Administration (NHTSA) develop and incorporate requirements into Federal Motor Vehicle Safety Standards (FMVSS) 213 specifying the BPB’s seating surface geometry and compressibility characteristics, including the seating surface compressibility requirement specified in the Canadian and Australian/New Zealand standards. In lieu of such requirements, the manufacturers of BPBs and automobiles must work together to ensure that the BPB component integrates properly with the seats and seat belt systems at all automobile occupant positions that can be used by a child to ensure that submarining is prevented.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".