Bibliographic record
Abstract
<div class="htmlview paragraph">The following two objectives were set for the development of predictions for snow ingress into the air intake system.</div> <div class="htmlview paragraph"> <ul class="list disc"> <li class="list-item"><div class="htmlview paragraph">To enable snow ingress predictions in the design stage so that vehicles can be developed in a short period of time.</div></li> <li class="list-item"><div class="htmlview paragraph">To guarantee performance in very cold regions such as Canada.</div></li> </ul> </div> <div class="htmlview paragraph">To achieve these objectives, it was decided to develop snow ingress prediction tools that use computational fluid dynamics (CFD). First, research was conducted in Canada to collect the snow information that was required for the simulation. In this research, snow particle measurement equipment was used to measure in detail the number of snow particles and their diameters. The research results that were obtained were reflected in the simulation, and a correlation was found between the calculations and test results obtained in Canada. Finally, tools were developed to facilitate results analysis from the snow ingress simulation. These analysis tools will be useful when formulating countermeasures against snow ingress or for deepening designer understanding of the phenomenon.</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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".