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Record W2945794744 · doi:10.1002/oa.2773

Archaeological and biometric perspectives on the development of chicken landraces in the Horn of Africa

2019· article· en· W2945794744 on OpenAlexaff
Helina Woldekiros, A. Catherine D’Andrea, Richard M. Thomas, Alison Foster, Ophélie Lebrasseur, Holly Miller, James Roberts, Naomi Sykes

Bibliographic record

VenueInternational Journal of Osteoarchaeology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock and Poultry Management
Canadian institutionsSimon Fraser University
FundersArts and Humanities Research Council
KeywordsFrench hornGallus gallus domesticusGeographyPeriod (music)PopulationAgricultureArchaeologyZoologyEthnologyBiologyDemographyHistoryArt

Abstract

fetched live from OpenAlex

Abstract Domestic chickens ( Gallus gallus domesticus L., 1758) were integrated into agricultural systems in the Horn of Africa as early as the pre‐Aksumite period (c. 2,500 years ago), after they were introduced from Asia through land and maritime trade and exchange. In this paper, we explore the development of chicken landraces in this region by examining continuity and change in chicken body size. Specifically, we compare the measurements of chicken bones dating from 800 BCE to 400 BCE from the pre‐Aksumite site of Mezber in northern Ethiopia, with those of modern chickens (of known age and sex) from northern Ethiopia and a population of known age and sex cross‐bred red junglefowl ( Gallus gallus L., 1758), curated at the Natural History Museum at Tring (UK). Considered together, these datasets provide insight into African poultry development and offer the first metrical baselines of chickens with known history in the region. Thus, this study has the potential to underpin future studies of domestic fowl morphology in Africa.

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 score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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Same venueInternational Journal of OsteoarchaeologySame topicLivestock and Poultry ManagementFrench-language works237,207