Bibliographic record
Abstract
By numerical calculation method,train going through tunnel and trains intersecting in the middle of tunnel at different speed( 200,250,300 and 350 km / h) were simulated,and gusts introduced by train was analyzed. Numerical calculation method was modified by the full- scale test data. The results show that,gusts caused by wake of train are the biggest. Gusts in tunnel are significantly influenced by the number of train carriages. Gusts introduced by 16- carriage train are greater than that of 8- carriage train,and the growth reaches70. 49%. It is an approximate linear relationship at nearby side and far side of train between the gusts speed and train speed when train passing through tunnel. While it is no longer linear relationship between gusts speed and variation of train speed when trains crossing in tunnel. The gusts introduced by trains crossing in tunnel is 1. 6times of one introduced by train going through tunnel. Two trains crossing in the middle of the tunnel have a certain influence on the amplitude of gusts. At the nearby side of train,gusts caused by train passing through the tunnel are bigger than that introduced by marshaling train crossing in the tunnel. At the far side of train,gusts caused by train meeting in the tunnel are bigger than that introduced by marshaling train passing through the tunnel.
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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".