MétaCan
Menu
Back to cohort
Record W6930464647 · doi:10.5281/zenodo.12573884

The Great Temple of Tenochtitlan

2024· article· en· W6930464647 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTempleHonorExcavationDowntownRepresentation (politics)Tower

Abstract

fetched live from OpenAlex

The Great Temple of Tenochtitlan was built by the Mexica (Aztecs) once they settled on an island (Tenochtitlan) in the Basin of Mexico during the Late Postclassic Period (1200-1521 CE). This temple was built to honor their patron deity, the sun and war god, Huitzilopochtli. This temple was placed at the center of the Mexica universe and religious cosmovision. It was rebuilt at least seven times during the several reigns of Mexica Emperors ("tlatoani"). It was approximately 47 m high and there were two shrines at the top, one dedicated to Huitzilopochtli and another to Tlaloc, the god of rain and earth's fertility. Since its discovery in 1978, the Templo Mayor Project team (PTM-INAH) have excavated this temple and its surroundings, uncovering over 200 sacred offerings filled with archaeological artifacts, ecofacts, and human remains. Each offering has its own meaning and representation in space and time (i.e., "cosmograma" in Spanish), depending on the type of ritual and the deity it was dedicated to. It's a very complex site with a lot more to find since part of it remains underneath the downtown core of present-day Mexico City making its excavation a challenge. All in all, this was the most sacred temple of the Mexica and everything revolved around this place as their most sacred precinct.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0250.002

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 head0.044
GPT teacher head0.271
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topic2D Materials and ApplicationsFrench-language works237,207