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Record W4399981965 · doi:10.1016/j.quaint.2024.05.008

Moche chronology of ancient Peru: Bayesian assessment of radiocarbon dates and ceramic styles from north to south

2024· article· en· W4399981965 on OpenAlexafffund
Michele L. Koons, Branden Rizzuto, Lisa Trever, Alicia Boswell, A. Perez, Luis A. Muro Ynoñán, Gabriel Prieto, Carlos Rengifo, Kayeleigh Sharp, Edward Swenson, Hugo Ikehara, Jessica Ortiz Zevallos, Tirza Cotrina Roncal, Richard J. George, José M. Capriles, Fuyuki Tokanai

Bibliographic record

VenueQuaternary International · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaStanford Institute for Research in the Social SciencesOffice of Research, University of GeorgiaOffice of Research, Graduate Studies and Economic Development, University of MissouriCollege of Liberal Arts and Sciences, University of ConnecticutUniversity of California, Santa BarbaraUniversity of TorontoDenver Museum of Nature and ScienceRust Family FoundationNational Geographic SocietyWenner-Gren Foundation
KeywordsRadiocarbon datingChronologyArchaeologyGeologyProxy (statistics)Bayesian probabilityGeographyComputer science

Abstract

fetched live from OpenAlex

In the last decade Bayesian analysis of radiocarbon dates has become commonplace for archaeologists grappling with regional chronologies. Here we present Bayesian analysis for radiocarbon dates from Moche cultural contexts from the north coast of Peru with the aim to understand the duration of the phenomenon and to compile all known dates in a single location for future analysis and use. The analysis demonstrates that the long-standing Moche ceramic sequence does not provide a perfect proxy for tracking the timing of all social interactions. However, our results show general agreement with traditional relative Moche chronologies. Finally, our study shows that Moche was a shorter cultural phenomenon than has been previously argued, with the current data indicating that it began between the late 4th and early 6th centuries CE and lasted until the 9th century CE.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.042
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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 teacher head, 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

Citations6
Published2024
Admission routes2
Has abstractyes

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