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Record W4399839881 · doi:10.25071/2561-5467.1163

A Petersen Type ‘M’ Sword in the Naval Academy’s Collections: Viking History Meets the Modern Navy

2024· article· fr· W4399839881 on OpenAlexvenueno aff
Jill Fitzgerald

Bibliographic record

VenueThe Northern Mariner / Le marin du nord · 2024
Typearticle
Languagefr
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
FundersU.S. Naval Academy
KeywordsSWORDNavyHistoryArtClassicsArchaeologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Sometime between 850-950 CE a 91cm single-edged sword was forged in Viking Age Norway. Eventually, that sword was placed in the earth, likely buried alongside its owner. Roughly 1,000 years later (in 1957), that sword was presented to the brigade of midshipmen at the United States Naval Academy by President Eisenhower. The artifact has the distinction of being the oldest weapon in the Naval Academy’s possession. This essay considers what forensic and archaeological evidence can tell us about the sword’s hitherto unknown history and also explores this artifact’s modern provenance and connection to US-Norwegian maritime relations in the mid-twentieth century. Entre 850 et 950 EC, une épée à un tranchant de 91 cm a été forgée dans la Norvège de l’ère des Vikings, puis elle a été enterrée, probablement aux côtés de son propriétaire. Environ 1 000 ans plus tard (en 1957), le président Eisenhower a présenté l’épée à la brigade d’aspirants de marine à l’Académie navale des États-Unis. L’artéfact a la particularité d’être la plus ancienne arme en la possession de l’Académie navale. Le présent article traite de ce que les preuves médico-légales et archéologiques peuvent nous dire au sujet de l’histoire jusqu’ici inconnue de l’épée et examine la provenance moderne de cet artéfact ainsi que son rapport aux relations maritimes américano-norvégiennes au milieu du 20e siècle.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.010
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.031
GPT teacher head0.227
Teacher spread0.196 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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