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Record W1983561842 · doi:10.1073/pnas.1100620108

Cacao use and the San Lorenzo Olmec

2011· article· en· W1983561842 on OpenAlexaff
Terry G. Powis, Ann Cyphers, Nilesh W. Gaikwad, Louis E. Grivetti, Kong Cheong

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCocoa and Sweet Potato Agronomy
Canadian institutionsTrent University
FundersDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoUniversidad Nacional Autónoma de MéxicoConsejo Nacional de Ciencia y TecnologíaNational Endowment for the HumanitiesNational Geographic SocietyAmerican Philosophical Society
KeywordsContext (archaeology)ArchaeologyPotteryMesoamericaGeographyHunter-gathererArtHistory

Abstract

fetched live from OpenAlex

Mesoamerican peoples had a long history of cacao use--spanning more than 34 centuries--as confirmed by previous identification of cacao residues on archaeological pottery from Paso de la Amada on the Pacific Coast and the Olmec site of El Manatí on the Gulf Coast. Until now, comparable evidence from San Lorenzo, the premier Olmec capital, was lacking. The present study of theobromine residues confirms the continuous presence and use of cacao products at San Lorenzo between 1800 and 1000 BCE, and documents assorted vessels forms used in its preparation and consumption. One elite context reveals cacao use as part of a mortuary ritual for sacrificial victims, an event that occurred during the height of San Lorenzo's power.

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 score0.032
Threshold uncertainty score0.063

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 studies0.0020.001
Scholarly communication0.0010.000
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 head0.085
GPT teacher head0.249
Teacher spread0.164 · 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

Citations97
Published2011
Admission routes1
Has abstractyes

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