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Record W4362628075 · doi:10.1002/oa.3225

The Preclassic military macaw (<scp><i>Ara militaris</i></scp>) from the Cueva de Avendaños (Chihuahua, Mexico) was not locally procured

2023· article· en· W4362628075 on OpenAlexfundno aff
J. Alberto Cruz, Eduardo Corona-M., Emiliano Gallaga

Bibliographic record

VenueInternational Journal of Osteoarchaeology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersInternational Network of Agencies for Health Technology Assessment
KeywordsMacawGeographyArchaeologyCaveRange (aeronautics)PopulationEthnologyEcologyBiologyDemographyHistory

Abstract

fetched live from OpenAlex

Abstract The oldest macaw specimen in Pre‐Hispanic Mexico and the southwestern United States was recovered in Cueva de Avendaños, Chihuahua, Mexico, at the base of the Sierra Madre Occidental. It dates to the Late Archaic/Early Agricultural period (1929–2057 cal BP). The head is the only preserved element of the macaw and it was mummified through natural causes. Research on this specimen examines its sex identification and its geographical range, questioning whether this specimen belongs to a local population living in the vicinity of the cave. A species distribution model over the last 2000 years was elaborated to ascertain the presence of military macaw in the study area. Our results show that the macaw was non‐local, sustaining the idea that the practice of early animal husbandry existed in the early stages of the Pre‐Hispanic world, and also suggest that a significant and rapid climate changes characterized the Holocene, affecting the military macaw's distributional range.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.243
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 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

Citations2
Published2023
Admission routes1
Has abstractyes

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