Citizen science monitoring of beach and dune erosion during Hurricane Fiona
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
Hurricane Fiona made landfall as an extra-tropical storm along the north shore of Prince Edward Island (PEI), Canada, in October 2022. The state of the beach and dune immediately before and after the storm was captured through the Coastie citizen science beach and dune photo monitoring initiative, as part of the global CoastSnap Community Beach Monitoring program. Coastie monitoring sites within Prince Edward Island National Park (PEINP) revealed extensive dune scarping, capturing a 12–17 m retreat of the foredune at Brackley and Cavendish Beaches. Using foredune scarp and post-storm shoreline positions, volumetric losses between 28 and 76 m3 m−1 are estimated from profiles located within the first 150 m of the stations. The average horizontal position of the projected foredune scarp position was within 2.8 m of the position identified from high accuracy unoccupied aerial system (UAS) surveys, corresponding to a mean absolute difference of 15.3 m3 m−1 or 45.3% for dune volume changes estimated from the images. Continued monitoring will yield further improvements to the volume loss estimation methodology, and insight on the timing and mechanisms of beach and dune recovery.
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 | 0.001 |
| 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