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Record W2612030020 · doi:10.1017/s0068113x17000216

‘Written in Bone’: New Discoveries about the Lives and Burials of Four Roman Londoners

2017· article· en· W2612030020 on OpenAlexafffund
Rebecca Redfern, Michael Marshall, Katherine Eaton, Hendrik N. Poinar

Bibliographic record

VenueBritannia · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsOsteologyContext (archaeology)Settlement (finance)Multidisciplinary approachHistoryWhite (mutation)GenealogyIdentity (music)Order (exchange)PaleopathologyArchaeologyAnthropologySociologyArtBiologyAestheticsSocial scienceGenetics

Abstract

fetched live from OpenAlex

Abstract The Museum of London selected four individuals for multidisciplinary scientific analyses in order to establish their ancestry, aspects of their personal appearance and health. We also reinterpreted their burial context in order to better understand how identity was constructed and expressed in this unique Roman settlement. Our study discovered the presence of people with Black and White European ancestry, some of whom had migrated from the southern Mediterranean. The most surprising result was that Harper Road woman's chromosomes were male. Overall, our experience of undertaking a multidisciplinary study served to further underline the need for these different techniques to be used in combination when investigating past identities. The mtDNA results were very broad and required the mobility isotopes to better understand their significance, while the aDNA evidence confirmed the osteological analysis. In terms of public engagement at the Museum of London, the ability to determine hair and eye colour had a significant impact.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0060.010
Scholarly communication0.0030.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.041
GPT teacher head0.272
Teacher spread0.231 · 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

Citations14
Published2017
Admission routes2
Has abstractyes

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