Environmental and Safety Performance of Commercially-available Light-duty Vehicle Tires in North America
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">New technology is enabling tire manufacturers to reduce tire rolling resistance, leading to reduced fuel consumption and greenhouse gas emissions in the transportation sector. This project analyzed current relationships between the environmental and safety performance of commercially-available light-duty tire models in North America. Performance data was rated using the EC No. 1222/2009, and compared against tire price, uniform tire quality grading standards (UTQG), and other attributes. A random selection of tire models was tested, consisting of: 108 all-season, 23 studless winter, and 5 all-weather tire models. All test results were blinded for the purpose of confidentiality. Tire rolling resistance coefficients were measured using the single point ISO 28580 standard, and wet grip index values were measured according to UN-ECE Reg.117. Rolling resistance and wet grip indicators were measured using dynamic mechanical analysis (DMA). Snow and ice traction ratings were calculated according to the ASTM F1805 procedure.</div><div class="htmlview paragraph">For the sample of all-season tires, no correlation was observed between rolling resistance and wet grip (0.004 &lt; =R<sup>2</sup> &lt;=0.065). For the sample of winter tires, a weak positive correlation was observed between rolling resistance and wet grip (R<sup>2</sup> = 0.189), indicating that lower rolling resistance values weakly predict lower wet grip values. A weak negative correlation between rolling resistance and snow traction (0.156 &lt;= R<sup>2</sup> &lt; 0.177) was observed, indicating that lower rolling resistance values weakly predict higher snow traction. For the sample of all-weather tires, there was a strong negative correlation between rolling resistance and wet grip (R<sup>2</sup>=0.708), indicating that lower rolling resistance coefficients strongly predict higher wet grip indices. There was also a strong positive correlation between rolling resistance and snow traction (0.769&lt;=R<sup>2</sup>&lt;0.779), indicating that lower rolling resistance coefficients strongly predict lower values of snow traction. When categorized according to the tire labeling standards from EC 1222/2009, sample populations trended towards the lower ends of the performance bins for both rolling resistance and wet grip.</div></div>
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".