Butchering Site Evolution Induced by Past and Recent Snowmelt Runoff: The Saunitarlik Site (JiEv‐15), Aivirtuuq Peninsula, Nunavik, Canada
Bibliographic record
Abstract
A geoarchaeological study of a unique Inuit site in Nunavik was undertaken in order to document the impact of humans on the Arctic environment. The Saunitarlik archaeological site is located on the Aivirtuuq peninsula near Kangiqsujuaq (Nunavik), and it was used as a butchering site by Inuit in the 19th century. It consists of an open‐air midden containing thousands of bones lying in the bed of an intermittent stream. This study documents the transformation of soil at the Saunitarlik site as a result of butchering activities by comparing them with extra‐site soils. Chronostratigraphic and sedimentological analyses of extra‐site sections show a succession of facies associated with: (1) till reworked by the sea, (2) regressive shoreline deposits, (3) surface runoff deposits, and (4) eolian deposits. Surface runoff deposits that dominate the peninsula were linked to regional climatic variations. Micromorphology analyses of intra‐ and extra‐site sediments revealed that periglacial and surface runoff were the main factors influencing site evolution. The intra‐site sections are characterized by the presence of dark, greasy, and sandy organic matter layers. Chemical analysis of these layers using gas chromatography‐mass spectrometry (GC−MS) indicated the presence of well‐preserved animal fatty acids in the sediments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 source (direct Gemma or distilled Codex), 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".