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Record W3022520919 · doi:10.1080/00438243.2019.1743205

Creating a body-subject in the Late Moche Period (CE 650 – 850). Bioarchaeological and biogeochemical analyses of human offerings from Huaca Colorada, Jequetepeque Valley, Peru

2020· article· en· W3022520919 on OpenAlexafffund
Aleksa K. Alaica, Luis Manuel González La Rosa, Kelly J. Knudson

Bibliographic record

VenueWorld Archaeology · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaWenner-Gren Foundation
KeywordsPeriod (music)ArchaeologyBiogeochemical cycleSubject (documents)HistoryGeographyEcologyArtBiology

Abstract

fetched live from OpenAlex

Human offerings in the archaeological record are commonly defined by their community affiliation, the ceremonial events following their death and the places where they are interred. The deposition of an individual links kin members to the landscape but also seems to mark time and memory. Here we argue that inter-generational memory, created through cyclical depositions of local, coastal community members at Huaca Colorada, reflects political alliances during the Late Moche Period of northern Peru. Using multiple lines of evidence, which include osteological, isotopic and burial context data, this article interprets the human offerings among the Moche of the Andes and argues that the significance of foundation offerings lies not exclusively in the spectacle of sacrifice, but in creating memory that maintains or transforms sacred landscapes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

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 studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.002
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 head0.065
GPT teacher head0.298
Teacher spread0.233 · 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

Citations9
Published2020
Admission routes2
Has abstractyes

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