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Record W2471420014 · doi:10.9750/psas.134.65.118

Excavations at Kaimes Hill, Ratho, City of Edinburgh, 1964 -72

2005· article· en· W2471420014 on OpenAlexfundno aff
D. D. A. Simpson, Richard Gregory, Eileen Murphy, Ann Clarke, L. E. Cram, Sarah Gormley, Nicholas Holmes, F. Robert Hunter, Martha McCartney, C McGill, Eiméar Nelis

Bibliographic record

VenueProceedings of the Society of Antiquaries of Scotland · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
FundersQueen's University BelfastQueen's UniversityMcGill University
KeywordsMesolithicExcavationArchaeologyRadiocarbon datingPrehistoryPeriod (music)HistoryGeographyAncient historyArt

Abstract

fetched live from OpenAlex

Kaimes Hill, City of Edinburgh, has been the focus for both antiquarian and modern archaeological research since at least the mid-nineteenth century and has produced evidence for activity dating from the Mesolithic through to the medieval period. The paper assimilates this evidence, provides a complete account of the excavations undertaken over the ramparts, `hut circles', prehistoric ritual and funerary monuments by D D A Simpson between 1964--72, and presents the results obtained from recent artefactual analysis and radiocarbon dating. Specialist reports include

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.010
GPT teacher head0.192
Teacher spread0.182 · 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

Citations4
Published2005
Admission routes1
Has abstractyes

Explore more

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