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Record W2402290094

Developing Minimally Impactful Protocols for DNA Analysis of Museum Collection Bone Artifacts

2016· dissertation· en· W2402290094 on OpenAlexaboutno aff
Kelly E. Brown

Bibliographic record

VenueSummit (Simon Fraser University) · 2016
Typedissertation
Languageen
FieldArts and Humanities
TopicConservation Techniques and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

This study has addressed the issue of destructive testing on museum collection artifacts from two perspectives. Firstly, interviews were conducted with museum professionals from across Canada to identify their specific concerns regarding access to their collections. Secondly, this information was then used to help develop a minimally impactful DNA sampling technique that may lead to greater access to museum collections for research. The development of this sampling technique involved successive rounds of testing conducted on bone samples including modern samples, unmodified archaeological samples, and museum artifacts from two different museums. The DNA sampling was done using a precision hand drill which produced a small amount of bone powder collected for analysis and species identification. The results from the study indicate that it was possible to develop a successful, comprehensive and reliable minimally impactful DNA sampling technique that is tailor-made to address the concerns and ethical responsibilities of museum professionals.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.272
Teacher spread0.227 · 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 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
Published2016
Admission routes1
Has abstractyes

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