Clear-water and live-bed scour depth modelling around bridge pier using support vector machine
Bibliographic record
Abstract
In recent history, local scour around the bridge piers has been a major cause of bridge failure; therefore, it is important to precisely predict the equilibrium scour depth. When the flow of water interacts with the bridge pier in the mobile bed, it usually results in local scour. In this paper, a total of 442 clear-water scouring (CWS) data and 300 live-bed scouring (LBS) data are collected from literature to model scour depth using a support vector machine. A sensitivity study was also carried out to assess the reliability of the model, and the strength of the proposed model is tested via an error analysis. The coefficient of determination ( R 2 ) value was found to be greater than 0.90 for both CWS and LBS. The present model is compared with more than 10 popular existing models and it has been discovered to be more reliable and efficient in estimating scour depth around bridge piers.
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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) | 0.000 | 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) | 0.001 | 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".