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Record W2766174213 · doi:10.1017/s0032247417000535

A comparative analysis of the Su-pung-er and Bayne testimonies related to the Franklin expedition

2017· article· en· W2766174213 on OpenAlexaboutno aff
Tom Gross, Russell S. Taichman

Bibliographic record

VenuePolar Record · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsVault (architecture)HistoryArchaeology

Abstract

fetched live from OpenAlex

ABSTRACT During Charles Francis Hall's second Arctic expedition (1864–1869) to find survivors and/or documents of Sir John Franklin's 1845 Northwest Passage expedition, two separate Inuit testimonies were recorded of a potential burial vault of a high-ranking officer. The first testimony was provided by a Boothia Inuk named Su-pung-er. The second testimony was documented by Captain Peter Bayne who, at the time, was employed by Hall. To date the vault has not been found. Recently, both the HMSErebusand HMSTerrorhave been located. The discovery of these vessels was made possible, in part, by Inuit testimony of encounters with and observations of the Franklin expedition. The findings of theErebusandTerrorhave significantly bolstered the view that the Inuit accurately reported their observations and interactions with the Franklin crew. The purpose of this paper is to publish in their entirety Hall's notes from conversations with Su-pung-er focused on the vaults and to compare these observations to those reported in the Bayne testimony. It is our hope that in so doing the final major archaeological site of the Franklin expedition may be located.

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)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.306
Teacher spread0.280 · 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 designQualitative
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

Citations6
Published2017
Admission routes1
Has abstractyes

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