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Record W2487082038 · doi:10.1484/m.cursor-eb.1.102214

Bioarchaeological Evidence of Stress and Activity in the Medieval Hrísbrú Cemetery in the Mosfell Valley, Iceland

2014· book-chapter· en· W2487082038 on OpenAlexaboutno aff
Jacqueline T. Eng

Bibliographic record

VenueCursor mundi · 2014
Typebook-chapter
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIcelandicViking AgeArchaeologyGeographyHistoryEthnologyAncient history

Abstract

fetched live from OpenAlex

The Viking North Atlantic differs significantly from the popular image of violent raids and destruction characterizing the Viking Age in Northern Europe. In Iceland, Scandinavian seafarers discovered and settled a large uninhabited island. In order to survive and succeed, they adapted lifestyles and social strategies to a new environment. The result was a new society: the Icelandic Free State. This volume examines the Viking Age in Iceland through the discoveries and excavations of the Mosfell Archaeological Project (MAP) in Iceland’s Mosfell Valley. Directed by Professor Jesse Byock with Field Director Davide Zori, MAP brings together scholars and researchers from Iceland, Britain, Canada, Denmark, Norway, Sweden, Germany, and the United States. The Project incorporates the disciplines of archaeology, history, saga studies, osteology, zoology, paleobotany, genetics, isotope studies, place-names studies, environmental science, and historical architecture. The decade-long research of MAP has led to the discovery of an exceptionally well-preserved Viking chieftain’s farmstead, including a longhouse, a pagan cremation site, a conversion-era stave church, and a Christian graveyard. The research results presented here tell the story of how the Mosfell Valley developed from a ninth-century settlement of Norse seafarers into a powerful Icelandic chieftaincy of the Viking 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.038
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.121
GPT teacher head0.289
Teacher spread0.169 · 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.

Study designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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