A process‐depositional model for the evaluation of archaeological potential and survey methods in a boreal forest setting, Northeastern Alberta, Canada
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
Abstract More than 1,000 archaeological sites occur within the Clearwater‐Athabasca Spillway, a relict channel that routed catastrophic drainage from glacial Lake Agassiz during deglaciation of northeastern Alberta. This high site density is rare in the region, and artifact assemblages are large due to the presence of abundant sources of lithic raw material. Unfortunately, sites are rarely preserved in stratified or deeply buried deposits. As is often the case in subarctic areas, this lack of depositional context coupled with a paucity of datable organic materials has hindered the establishment of cultural chronologies for the region. To address this issue, we develop a process‐depositional model and digital terrain analysis to identify where thicker sediments may have accumulated, and assess whether survey strategies have adequately tested these areas. We find current survey strategies are biased to testing upland ridges with thin deposits, and that inconsistent methods of recording sediment thickness make it difficult to assess whether vertical profiles are being sampled to sterile deposits. We recommend that future survey strategies in boreal forest settings focus on a broader suite of landforms and landform elements, including those that act as sediment traps.
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 | 0.004 | 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 | 0.001 |
| 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