Impacts of past and future coastal changes on the Yukon coast — threats for cultural sites, infrastructure, and travel routes
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
Yukon’s Beaufort coast, Canada, is a highly dynamic landscape. Cultural sites, infrastructure, and travel routes used by the local population are particularly vulnerable to coastal erosion. To assess threats to these phenomena, rates of shoreline change for a 210 km length of the coast were analyzed and combined with socioeconomic and cultural information. Rates of shoreline change were derived from aerial and satellite imagery from the 1950s, 1970s, 1990s, and 2011. Using these data, conservative (S1) and dynamic (S2) shoreline projections were constructed to predict shoreline positions for the year 2100. The locations of cultural features in the archives of a Parks Canada database, the Yukon Archaeological Program, and as reported in other literature were combined with projected shoreline position changes. Between 2011 and 2100, approximately 850 ha (S1) and 2660 ha (S2) may erode, resulting in a loss of 45% (S1) to 61% (S2) of all cultural features by 2100. The last large, actively used camp area and two nearshore landing strips will likely be threatened by future coastal processes. Future coastal erosion and sedimentation processes are expected to increasingly threaten cultural sites and influence travelling and living along the Yukon 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) | 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