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Record W4361803159 · doi:10.3828/hgr.2019.10

Using lipid residues to interpret past alpine diet and subsistence in northwestern Wyoming

2019· article· en· W4361803159 on OpenAlexaff
Matthew Stirn, Rebecca Sgouros, Mary E. Malainey

Bibliographic record

VenueHunter Gatherer Research · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsBrandon University
Fundersnot available
KeywordsSubsistence agricultureGeographyArchaeologyTerrainHunter-gathererEcosystemEcologyBiologyAgriculture

Abstract

fetched live from OpenAlex

The investigation of diet and subsistence practices is pivotal in aiding our understanding of how and why hunter-gatherers utilised high-elevation landscapes. However, preservation issues in alpine terrain leave relatively little physical evidence of foods. Lipid residues offer a solution to this issue as they are resilient to many destructive forces, are found in alpine landscapes and can be reliably identified within porous artifacts. By using non-destructive lipid residue analysis on steatite, groundstone and ceramic artifacts from sites across three mountain ranges in the Greater Yellowstone Ecosystem, the results of this study offer a glimpse into prehistoric alpine cuisine, finding that hunter-gatherers consumed a diverse suite of plant and animal resources over the past 6000 years.

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)0.001
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 score0.358
Threshold uncertainty score0.712

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.316
Teacher spread0.248 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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