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1. Introduction

2012· article· en· W4232430675 on OpenAlexaboutno aff
Jónas Kristjánsson, Bjarni F. Einarsson, Kristján Jónasson, Kevin McAleese, Þór Hjaltalín

Bibliographic record

VenueActa Archaeologica · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Archaeological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIcelandicViking AgeArchaeologyRadiocarbon datingSettlement (finance)HistoryGeographyBayAncient history

Abstract

fetched live from OpenAlex

Two interwoven topics are dealt with, firstly a new interpretation of the Icelandic Sagas and historical written sources on the Viking age voyages to North America, leading to a theory on the location of Vínland, and secondly an archaeological survey of deer hunting pitfalls in Newfoundland, which were possibly dug by the Nordic voyagers a millenium ago. According the theory of the article, Vínland is the modern day Newfoundland, and the Straumfjord of the sagas, where Thorfinn Karlsefni and Gudríd Thorbjarnardóttir attempted settlement could be Sop’s Arm in White Bay on the North coast of Newfoundland. The system of pitfalls that was surveyed and excavated is close to Sop’s Arm. The pitfalls form an 82 metre long system that lies in an almost straight line. Individual pits are now 1.5–2.3 metres deep and 7–10 metres long. Two pitfalls were excavated by taking a section into them. Attempted radiocarbon dating of soil from two pitfalls was inconclusive. Considerable soil thickening of 55–110 centimetres since the pitfall construction was observed.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.600
Threshold uncertainty score0.856

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0080.005
Open science0.0020.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.4000.282

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 head0.041
GPT teacher head0.215
Teacher spread0.174 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2012
Admission routes1
Has abstractyes

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