Bibliographic record
Abstract
This project aims to re-assess our understanding of the shape of fluvial bedload gravels by drawing together existing information on fluvial gravel shape. At its crux, however, is the interpretation of a large, high-quality set of measurements made on bedload gravels from the Sabeto River of western Viti Levu, Fiji. This work reveals that the apparent simplicity displayed by most studies of downstream rounding disguises a complex pattern of stepwise reversals to an angular state, the result of the splitting of cobble- and boulder-sized particles. Particle sphericity changes rapidly during the initial stages of transport. Along the Sabeto, this seems to be the result of attrition, with breakage generating the low and continuing presence of low sphericity particles in the system. Elsewhere, however, sphericity is a consequence of shape sorting and we speculate that rivers globally exist along a sorting–attrition continuum. The form of fluvial gravels is not what would be expected were sorting the dominant control on gravel form. Instead measurements of form display a complex relationship with roundness (and thus with breakage and abrasion). Fluvial gravels appear to evolve to a distinctive shape that may offer a means of distinguishing the products of riverine deposition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".