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Record W4402290416 · doi:10.1177/09596836241266408

Humans and climate in ritualized landscapes, the case of Lake Tota in the eastern highlands of Colombia

2024· article· en· W4402290416 on OpenAlexaff
María I. Vélez, Jorge Salgado, Miguel Delgado, Luisa Fernanda Patiño, Broxton W. Bird, Jaime Escobar, Sebastian Fajardo

Bibliographic record

VenueThe Holocene · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Cultural Studies in Latin America and Beyond
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsGeographyClimate changeArchaeologyPhysical geographyGeologyOceanography

Abstract

fetched live from OpenAlex

Tota is an Andean lake located in the Altiplano of the Eastern Andes of Colombia where socio-politically hierarchical societies of the Herrera and Muisca, flourished for millennia. To them, the lake and surrounding forest were places used for diverse of activities including religious rituals. In this study we produced a multi-proxy paleolimnological reconstruction using diatoms, isotopes, and geochemistry, to try to understand the lake’s pathways of change in response to natural climatic variations and anthropogenic activities. The diatom record is dominated by tychoplanktonic Staurosirella dubia and planktonic Aulacoseira species including species A. cf lirata, A. granulata, A. distans, and A. ambigua. Diatoms were grouped into functional groups and used to infer limnological changes that were further complemented with the geochemistry of the sediments to reconstruct the past environment. Results show three main periods in which the lake changed significantly, these are dated from ~800 to 1200, 1200 to 1500, and 1500 to 1900 CE. A correlation with the archeological record of the region, ethnohistoric accounts and climate suggests that these changes occurred simultaneously with changes in archeological stages, the Spanish arrival, and more recently by the industrial revolution, and the Little Ice Age.

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 score0.096
Threshold uncertainty score0.308

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)0.0000.000

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 head0.241
Teacher spread0.232 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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