Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of aerial photographs to estimate short-term shoreline changes, i.e. coastal changes at a monthly scale reflecting seasonal changes in the underlying hydrodynamics, is presented in this paper. To achieve this a data set of seven vertical aerial photographs with a time span of four months, taken at the Ebro delta (NE Spanish Mediterranean coast) has been used. The method was applied to the analysis of very flat areas, highly dynamic coastal features, storm impacts and to the entire deltaic coast. Although the study area is a microtidal environment, obtained results of the very flat areas analysis do not recommend its use at very short time scales due to meteorological tide influences. The formation, erosion and re-formation of a spit at the river mouth was easily monitored being controlled the evolution of its length, perimeter and subaerial surface. Aerial photos permitted to identify vulnerable zones to impacts of very energetic storms by characterising breaching events along the coast (location and magnitude). Finally, when the method was applied to the entire deltaic coast, a detailed seasonal and spatial distribution of shoreline changes was obtained. The comparison of shoreline rates of change obtained from photos with that obtained from beach profiles shows that the method is reasonably accurate at least for the Ebro delta coast.
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.
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) | 1.000 | 0.999 |
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