Archaeological documentation of wood caribou fences using unmanned aerial vehicle and very high-resolution satellite imagery in the Mackenzie Mountains, Northwest Territories
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
Indigenous peoples of Canada’s North have long made use of boreal forest products, with wooden drift fences to direct caribou movement towards kill sites as unique examples. Caribou fences are of archaeological and ecological significance, yet sparsely distributed and increasingly at risk to wildfire. Costly remote field logistics requires efficient prior fence verification and rapid on-site documentation of structure and landscape context. Unmanned aerial vehicle (UAV) and very high-resolution (VHR) satellite imagery were used for detailed site recording and detection of coarse woody debris (CWD) objects under challenging Subarctic alpine woodlands conditions. UAVs enabled discovery of previously unknown wooden structures and revealed extensive use of CWD (n = 1745, total length = 2682 m, total volume = 16.7 m 3 ). The methodology detected CWD objects much smaller than previously reported in remote sensing literature (mean 1.5 m long, 0.09 m wide), substantiating a high spatial resolution requirement for detection. Structurally, the fences were not uniformly left on the landscape. Permafrost patterned ground combined with small CWD contributions at the pixel level complicated identification through VHR data sets. UAV outputs significantly enriched field techniques and supported a deeper understanding of caribou fences as a hunting technology, and they will aid ongoing archaeological interpretation and time-series comparisons of change agents.
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 | 0.001 | 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 | 0.001 |
| 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