Low Rolling Resistance Tires TEST PLAN
Bibliographic record
Abstract
Transport Canada’s ecoTECHNOLOGY for Vehicles program (―eTV‖) tests emerging vehicle technologies to assess their performance in accordance with established Canadian motor vehicle standards. The test plan presented herein does not, in itself, represent an official determination by Transport Canada regarding fuel consumption or compliance with safety and emission standards of any motor vehicle or motor vehicle component. Transport Canada does not certify, approve or endorse any motor vehicle product. Technologies selected for evaluation, and test results, are not intended to convey policy or recommendations on behalf of Transport Canada or the Government of Canada. Transport Canada and more generally the Government of Canada make no representation or warranty of any kind, either express or implied, as to the technologies selected for testing and evaluation by eTV, nor as to their fitness for any particular use. Transport Canada and more generally the Government of Canada do not assume nor accept any liability arising from any use of the information and applications contained or provided on or through these test results. Transport Canada and more generally the Government of Canada do not assume nor accept any liability arising from any use of third party sourced content.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.050 | 0.028 |
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".