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Record W4366339445 · doi:10.1017/s0956536121000651

Nueva perspectiva sobre el sistema de organización territorial epiclásico en la región de Zacapu, Michoacán

2023· article· es· W4366339445 on OpenAlexaff
Grégory Pereira, Antoine Dorison, Osiris Quezada Ramírez, Céline Gillot, Dominique Michelet

Bibliographic record

VenueAncient Mesoamerica · 2023
Typearticle
Languagees
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsMcMaster University
FundersCentre National de la Recherche ScientifiqueMinistère de l'Europe et des Affaires ÉtrangèresAgence Nationale de la Recherche
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Resumen El período de aproximadamente tres siglos (600–900 d.C.), que corresponde al epiclásico, fue el escenario de una notable expansión de los asentamientos en la cuenca de Zacapu y sus alrededores. Si bien la zona parecía carecer de núcleos monumentales mayores equivalentes a los que se conocían en las regiones vecinas del Bajío o del sur de las tierras altas michoacanas, los trabajos recientes en la parte noroeste del Malpaís de Zacapu cambian esta concepción. Los datos proporcionados por medio del LiDAR y nuevos trabajos de campo revelaron complejos monumentales de dimensiones inéditas para la zona que estructuran una red de asentamientos menores distribuidos en un amplio territorio. Estos descubrimientos ofrecen nuevos datos sobre la arquitectura pública y doméstica de la época. La distribución de estos asentamientos y su relación con áreas dedicadas a la explotación de recursos agrícolas y mineros permiten vislumbrar un sistema más complejo e integrado, el cual pudo tener elementos comunes al de un altepetl. El objetivo de este artículo es presentar esta nueva información y reevaluar, a partir de ella, la organización territorial del período considerado.

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)0.001
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 score0.370
Threshold uncertainty score0.736

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.282
Teacher spread0.268 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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