Untangling natural and anthropogenic multi‐element signatures in archaeological soils at the Ikirahak site, Arctic Canada
Bibliographic record
Abstract
Multi‐element archives housed within archaeological soils and sediments are useful for identifying ancient human activities invisible to routine methodologies. These records, however, are rarely studied in the Canadian Arctic. Contributing to this area of research, we address the fundamental issue of isolating natural and anthropogenic multi‐element signatures in archaeological soils from the region. We specifically investigated the element record in the soil system at the Ikirahak site, a Taltheilei hunter‐gatherer camp in southern Nunavut that was established roughly 2000 years ago. Ikirahak soils displayed high potential for the preservation of anthropogenic element additions. This owes to the fine textures, high cation adsorbance capacities and acidic pH levels of the local soils, as well as the absence of processes such as brunification and solifluction. Multi‐element characterization was accomplished using x‐ray fluorescence and inductively coupled plasma ‐ mass spectroscopy. Several locations with anomalous concentrations were pinpointed using enrichment factors. Natural and anthropogenic signals were untangled using categorical principal components analysis of a mixed quantitative/qualitative data set comprised of the element concentrations and contextual information such as the presence of specific archaeological materials, organic matter content, and vegetation communities. Results indicated that enrichments in CaO, P 2 O 5 , Ba, Fe 2 O 3 , MnO, Cu and Sc across the site relate to the disposal of burned refuse that was produced in pit‐house hearths. Concentrations of Li, Na, K, Rb and Cs (alkali metals), Mg and Sr (alkaline earths), Ti, V, Cr, Ni, Zn, Y, Zr, Nb, Mo and Hf (transition metals), Al, Ga and Pb (post‐transition metals), and La, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu (rare earths) were linked to esker and lacustrine parent sediments.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".