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Record W2785101484

A Case Study of the Mayan Civilization and Strategies Used by Mayan Society for Judicious Use of Water in their Ancient Agroecological Systems

2017· article· en· W2785101484 on OpenAlexaff
Julia Wright, Magnolia Tzec-Gamboa, Francisco Javier Solorio Sánchez, Luis Ramírez-Avilés, Immo Fiebrig, Manuel Pulido Fernández, Saikat Basu

Bibliographic record

VenuePure (Coventry University) · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMexican Socioeconomic and Environmental Dynamics
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsAgroecologyCivilizationEnvironmental ethicsGeographyHistoryArchaeologyPhilosophyAgriculture
DOInot available

Abstract

fetched live from OpenAlex

The Mayan civilization is one of the best known ancient cultures that inhabited Mesoamerica. It originated around 2600 BC in the Yucatan Peninsula, El Salvador, Belize and Honduras. Recent research indicates the devastating impacts of climate change on this culture. Researchers found signs of historic droughts that affected Mayan society, and the information provides answers to longstanding questions about the role climate change played in Mayan cultural collapse. The dominant agricultural systems of the Mayan civilization were mostly intensive farming systems based on a rotational slash and burn process. Most of their crops were grown on a rotational pattern for their own consumption, and comprised mostly maize, squash and beans. When the soil lost its fertility, Mayan farmers applied slash and burn on a new area of the local forest; meanwhile the abandoned area recovered its fertility under period of fallow when the forest regenerated. The current review highlights the available information on the impact of the Mayans on the natural resources and the impact of climate change on ancient Mayan society.

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 score0.310
Threshold uncertainty score0.258

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 head0.023
GPT teacher head0.200
Teacher spread0.176 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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