HOW INCIPIENT MOTION DETERMINATION JUDGMENT AFFECTS DIFFERENT PARAMETERS IN SEDIMENT TRANSPORT INVESTIGATION
Bibliographic record
Abstract
Abstract: Incipient condition plays a significant role in the field of sediment transport and channel stability and different parameters based upon it are used in the sediment initiation and transport formulas both for the development and application purposes. Its determination depends upon the subjective judgment of the investigator. Effects of this judgment on sediment transport and flow parameters have been investigated in this paper by considering three flow conditions of M (when small number of particles start to move), M1 (when large number of particles starts to move), and M2 (when very large number of particles starts to move). Data used in this paper were collected from a sediment transport study conducted in the hydraulics laboratory of the University of Manitoba (Canada). Effects of each flow condition on sediment transport, critical discharge, critical velocity, and flow depth parameters were investigated and a significant variation in results was found when flow conditions varied. This variation was more pronounced with the smaller sediment sizes as compared to the larger ones. For the critical discharge, a difference between M and M1, M1 and M2 and M and M2 conditions ranged from 36-118%, 16-129 % and 61-211%, respectively. Likewise, other parameters of flow depth, critical velocity, sediment loads were significantly affected when the conditions were altered. Among the three conditions the M1 appeared to be more reliable and realistic to be used for the incipient motion determination.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".