The threshold effect of image resolution on image‐based automated grain size mapping in fluvial environments
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Bibliographic record
Abstract
Abstract It has recently been demonstrated that surficial grain sizes in fluvial environments could be derived with automated methods applied to airborne digital imagery having a ground resolution of 3 cm. This letter seeks to further examine the potential of digital imagery for automated grain size mapping. In order to broaden the application of automated grain size mapping from airborne imagery, the effect of image resolution needs further study. Automated grain size mapping was attempted on an airborne digital image with a ground resolution of 10 cm. The results show that meaningful grain size information can be derived from 10 cm imagery. However, the ground resolution of the image acts as a size threshold below which no grain size information is detectable. Therefore, these results strongly suggest that future applications of automated grain size mapping will always be dependent on the ground resolution made available by the technology in use at the time of image acquisition. Copyright © 2005 John Wiley & Sons, Ltd.
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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) | 0.000 | 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 it