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Record W2980617547 · doi:10.1002/gea.21751

The origin of smectite in the soil of the Kruger 2 archaeological site, Brompton (Québec), Canada

2019· article· en· W2980617547 on OpenAlexaffabout
François Courchesne, Claude Chapdelaine, Lara Munro

Bibliographic record

VenueGeoarchaeology · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsWeatheringChloriteClay mineralsHearthMicaGeologyMineralCalciteApatiteMineralogyDissolutionGeochemistryHorizonSoil waterChemistryArchaeologySoil sciencePaleontologyGeography

Abstract

fetched live from OpenAlex

Abstract Kruger 2 is unique among Late Paleoindian sites of eastern Canada because of the presence of a potential hearth (feature #1) characterized by a concentration of blackened fire‐cracked rock and burnt bone embedded in a thick Ae horizon. Comparative mineralogical analysis (X‐ray diffraction) of Ae samples collected inside and outside the feature reveal the absence of calcite and apatite, two minerals commonly found in ashes, and the presence of smectite in the Ae inside feature #1. Smectite genesis is attributed to the weathering of mica and chlorite under geochemical conditions (high base cations, Si and pH; low Al) that are unique in time and space. We hypothesize that these conditions were created by the dissolution, 10,000 years ago, of a layer of hearth ashes resting on an incipient soil. Results confirm the intense weathering of mica and chlorite. We also show that ash dissolution could generate the conditions for smectite formation in the presence of altered mica and chlorite, allowing the development of a chronology explaining this finding. The data largely support our hypothesis and constitute a strong basis for future investigations on the links between hearth ash weathering and smectite genesis in acidic soils.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.006
GPT teacher head0.177
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2019
Admission routes2
Has abstractyes

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