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Record W2097501157 · doi:10.1017/s0003581510000028

<i>Prehistoric Annals</i>and Early Medieval Monasticism: Daniel Wilson, James Young Simpson and their Cave Sites

2010· article· en· W2097501157 on OpenAlexfundno aff
Kristján Ahronson, Т. Μ. Charles-Edwards

Bibliographic record

VenueThe Antiquaries Journal · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies of British Isles
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaBritish Academy
KeywordsMonasticismCaveAnnalsPrehistoryHistoryMiddle AgesArchaeologyAncient historyGeographyClassics

Abstract

fetched live from OpenAlex

Abstract To deepen our understanding of early medieval exile, the present study characterizes ways in which scholars have studied cave use in Britain and Ireland. As key figures in the history of archaeology, Sir Daniel Wilson and Sir James Young Simpson were crucial for establishing Scotland’s cave sites as subjects for study. Triggered by these two, a century and a half of research has related these places to the flowering of Gaelic monasticism. Nonetheless, fundamental similarities between early Christian communities in Britain and Ireland are at odds with this northern distribution, and bring the question of cave use beyond Scotland sharply into focus. Our paper therefore targets two questions: (1) to what extent were cave sites used by early Christian communities elsewhere in the Insular world; and (2) is our perception of cave use as a particularly north British phenomenon skewed by the long history of Scottish interest in the topic?

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.016
Scholarly communication0.0050.002
Open science0.0010.003
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 head0.022
GPT teacher head0.217
Teacher spread0.195 · 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 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

Citations2
Published2010
Admission routes1
Has abstractyes

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