Experimental research of car acceleration characteristics
Bibliographic record
Abstract
This paper describes an experimental research of car acceleration characteristics with evaluation of influence of traction control systems (further TCS). The main purpose of these experiments was to examine values of longitudinal car acceleration characteristics on different road pavements with efficiency evaluation of different TCS the “XL Meter Pro Gamma” accelerometer was used for the experiments. As an important active TCS was used in the experiments, the obtained results enable evaluation of influence of car wheel slip on car acceleration characteristics as well as on car control when such slip happens on different road pavements (dry asphalt-concrete, snow-covered asphalt-concrete). Analysis of car acceleration characteristics enables to research the controllability of front drive cars – the level of ability to pass by an obstacle with acceleration. The obtained and analysed results can be useful to experts and professionals analyzing road accidents. These results enable to found acceleration characteristics in some realistic situations and evaluate, had the driver a technical possibility to avoid the road accident.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".