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Record W4362466320 · doi:10.1126/science.adc9691

Early dispersal of domestic horses into the Great Plains and northern Rockies

2023· article· en· W4362466320 on OpenAlexaff
William Taylor, Pablo Librado, Mila Hunska Tašunke Icu, Carlton Shield Chief Gover, Jimmy Arterberry, Anpetu Luta Wiƞ, Akil Nujipi, Tanka Omniya, Mario González, Bill Means, Sam High Crane, Barbara Dull Knife, Wakiƞyala Wiƞ, Cruz Tecumseh Collin, Chance Ward, Theresa A. Pasqual, Loreleï Chauvey, Laure Tonasso‐Calvière, Stéphanie Schiavinato, Andaine Seguin‐Orlando, Antoine Fages, Naveed Khan, Clio Der Sarkissian, Xuexue Liu, Stefanie Wagner, Beth Leonard, Bruce L. Manzano, Nancy O’Malley, Jennifer A. Leonard, Eloísa Bernáldez Sánchez, Éric Barrey, Léa Charliquart, Émilie Robbe, Thibault Denoblet, Kristian Murphy Gregersen, Alisa O. Vershinina, Jaco Weinstock, Petra Rajić Šikanjić, Marjan Mashkour, Irina Shingiray, Jean‐Marc Aury, Aude Perdereau, Saleh A. Alquraishi, Ahmed Alfarhan, Khaled A. S. Al‐Rasheid, Tajana Trbojević Vukičević, Marcel Burić, Eberhard Sauer, Mary Lucas, Joan Brenner Coltrain, John R. Bozell, Cassidee A. Thornhill, Victoria Monagle, Angela Perri, Cody Newton, William E. Hall, Joshua L. Conver, Petrus le Roux, Sasha G. Buckser, Caroline Gabe, Juan Bautista Belardi, Christina I. Barrón-Ortiz, Isaac Hart, Christina Ryder, Matt Sponheimer, Beth Shapiro, John Southon, Joss Hibbs, Charlotte Faulkner, Alan K. Outram, Laura Patterson Rosa, Katelyn Palermo, Marina Solé, Alice William, Wayne McCrory, Gabriella Lindgren, Samantha A. Brooks, Camille Eché, Cécile Donnadieu, Olivier Bouchez, Patrick Wincker, Gregory Hodgins, Sarah Trabert, Brandi Bethke, Patrick Roberts, Emily Lena Jones, Yvette Running Horse Collin, Ludovic Orlando

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsGovernment of CanadaRoyal Alberta Museum
FundersUniversidad Nacional de la Patagonia AustralTaif UniversityIdaho State UniversityMax-Planck-GesellschaftKing Saud UniversityAlMaarefa UniversityPrincess Nourah Bint Abdulrahman UniversityUniversity of WyomingBureau of ReclamationAgence Nationale de la RechercheConsorzio Interuniversitario BiotecnologieU.S. Department of AgricultureEuropean CommissionNational Science Foundation
KeywordsBiological dispersalGeographyArchaeologyDemography

Abstract

fetched live from OpenAlex

The horse is central to many Indigenous cultures across the American Southwest and the Great Plains. However, when and how horses were first integrated into Indigenous lifeways remain contentious, with extant models derived largely from colonial records. We conducted an interdisciplinary study of an assemblage of historic archaeological horse remains, integrating genomic, isotopic, radiocarbon, and paleopathological evidence. Archaeological and modern North American horses show strong Iberian genetic affinities, with later influx from British sources, but no Viking proximity. Horses rapidly spread from the south into the northern Rockies and central plains by the first half of the 17th century CE, likely through Indigenous exchange networks. They were deeply integrated into Indigenous societies before the arrival of 18th-century European observers, as reflected in herd management, ceremonial practices, and culture.

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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.230
Teacher spread0.221 · 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

Citations46
Published2023
Admission routes1
Has abstractyes

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