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Record W2313822159 · doi:10.3998/jar.0521004.0071.204

Ancient Use of Coca Leaves in the Peruvian Central Highlands

2015· article· en· W2313822159 on OpenAlexaff
Lidio M. Valdéz, Juan Taboada, J. Ernesto Valdez

Bibliographic record

VenueJournal of Anthropological Research · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicLatin American history and culture
Canadian institutionsMacEwan University
Fundersnot available
KeywordsCocaContext (archaeology)ArchaeologyGeographyAncient historyHistory

Abstract

fetched live from OpenAlex

Coca, of the genus Erythroxylum, is a stimulant and painkiller that played key roles within the Inka state. As reported by the early Spanish chroniclers, coca was the most important plant offering during public rituals. Likewise, important landmarks within the Inka domain regularly received offerings of this precious leaf. Its high value is indicated by the fact that not only the living chewed the leaves on a regular basis, but also the dead carried coca leaves in their mouths. We still do not know when coca leaves were first used in the Peruvian central highlands. This uncertainty is largely due to the lack of coca leaves recovered from highland archaeological sites. Several leaves recently found at Convento in the northern part of the Ayacucho Valley are the first direct evidence from an archaeological context that, based on ceramic stylistic grounds, dates to sometime between the end of the Early Intermediate Period (ca. 1–550 ce) and the beginning of the Middle Horizon Period (ca. 550–1100 ce). The botanical identification also indicates that the source of the coca was the Pacific coast. This paper reports this unique finding and discusses its implications.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.516
GPT teacher head0.422
Teacher spread0.093 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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