Bed-load transport model based on fractional size distribution
Bibliographic record
Abstract
Two models based on the fractional size distribution approach, used in conjunction with the excess discharge theory, have been developed by using bed-load data collected from the Roaring River (Rocky Mountain National Park, Colorado) during the summer of 1995. The first model is based on the critical discharge value of individual fractional (IF) sizes, IF model (for log-normal and nonlog-normal size distribution modes), while the other is based on critical discharge value for total (combined) sizes, total fractional (TF) sizes model (for log-normal and nonlog-normal size distribution modes). The performance of the log-normal size distribution based models was tested with data from the Roaring River, Rich Creek, and Fourmile Creek (three Colorado streams), whereas the performance of the nonlog-normal size distribution based models was tested using Pitzbach River data. The performance of the models was also tested by comparing their results with the Inpasihardjo fractional size distribution based model. For all tests, the TF model performed better for both the log-normal and nonlog-normal grain size distributions.Key words: fractional size, critical discharge, IF model, TF model, discharge theory, Roaring River.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".