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Record W2901403213 · doi:10.1017/ppr.2018.14

When and Why? The Chronology and Context of Flint Mining at Grime’s Graves, Norfolk, England

2018· article· en· W2901403213 on OpenAlexaboutno aff
Frances Healy, Peter Marshall, Alex Bayliss, Gordon Cook, Christopher Bronk Ramsey, J. van der Plicht, Elaine Dunbar

Bibliographic record

VenueProceedings of the Prehistoric Society · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
Fundersnot available
KeywordsBeakerRadiocarbon datingChronologyBronze AgeArchaeologyPotteryPeriod (music)Context (archaeology)Quarter (Canadian coin)BronzeChalcolithicAncient historyGrave goodsMiddle AgesHistoryGeographyArt

Abstract

fetched live from OpenAlex

New radiocarbon dating and chronological modelling have refined understanding of the character and circumstances of flint mining at Grime’s Graves through time. The deepest, most complex galleried shafts were worked probably from the third quarter of the 27th century cal bc and are amongst the earliest on the site. Their use ended in the decades around 2400 cal bc , although the use of simple, shallow pits in the west of the site continued for perhaps another three centuries. The final use of galleried shafts coincides with the first evidence of Beaker pottery and copper metallurgy in Britain. After a gap of around half a millennium, flint mining at Grime’s Graves briefly resumed, probably from the middle of the 16th century cal bc to the middle of the 15th. These ‘primitive’ pits, as they were termed in the inter-war period, were worked using bone tools that can be paralleled in Early Bronze Age copper mines. Finally, the scale and intensity of Middle Bronze Age middening on the site is revealed, as it occurred over a period of probably no more than a few decades in the 14th century cal bc . The possibility of connections between metalworking at Grime’s Graves at this time and contemporary deposition of bronzes in the nearby Fens is discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.011
GPT teacher head0.175
Teacher spread0.164 · 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.

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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

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