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Record W6998876479

An Artifact and Spatial Analysis of South Branch House (FfNm-1)

2022· dissertation· en· W6998876479 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArtifact (error)BayField (mathematics)Range (aeronautics)Work (physics)
DOInot available

Abstract

fetched live from OpenAlex

The archaeological site FfNm-1 (South Branch House) is a late 1700s fur trade site located on the South Saskatchewan River in Central Saskatchewan. Its construction is attributed to the Hudson’s Bay Company fur trade post of the same name, dating to between 1786-1794. Between the years of 2005 and 2014 the Saskatchewan Archaeological Society operated a series of public field schools with the purpose of excavating this site and exposing the public to a hands-on archaeological experience. The results of these field schools recovered over 24,000 artifacts and excavated 215 units. The identity, corporate affiliation and occupation dates of the site were called into question prior to the completion of the field schools. Today, after nearly a decade of field work on this site has taken place, the large quantity of data offers an excellent opportunity to re-evaluate what is known about FfNm-1. The following thesis contributes to this re-evaluation through a functional analysis of the site’s artifacts and GIS-based horizontal and vertical analyses of artifact distribution. Through multiple lines of evidence these analyses successfully determined a range of occupation dates at the site, as well as provided tentative corporate affiliations. It was further determined that while more information is needed, the site is consistent with what would be expected at the Hudson’s Bay Company’s South Branch House.

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)0.000
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 score0.773
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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