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Record W2528837212 · doi:10.2218/jls.v3i2.1444

Introducing LIR (Lithotheque Ireland), a reference collection of flaked stone tool raw materials from Ireland

2016· article· en· W2528837212 on OpenAlexafffund
Killian Driscoll, Adrian L. Burke, Graeme Warren

Bibliographic record

VenueJournal of Lithic Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsUniversité de Montréal
FundersUniversité de MontréalIrish Research CouncilUniversity of GalwayUniversity College DublinGovernment of CanadaNational University of IrelandNational Geographic Society
KeywordsProspectionPetrographyArchaeologyGeologyStone toolCretaceousMetadataDatabaseGeographyPaleontologyWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

The LIR (Lithotheque Ireland) reference collection of flaked stone tool raw materials from Ireland began in 2013, and is based on the geological prospection from two projects. The first (2013-2015) focused attention primarily on Carboniferous cherts from the northwest of Ireland, collecting 405 samples. The second (2015-2017) is currently collecting samples of the Cretaceous flint primarily from in situ contexts in the northeast of Ireland, but also includes beach surveys of Cretaceous flint from around the island; the first phase of geological prospection in Autumn 2015 collected 239 samples, with the geological prospection continuing in 2016. Therefore, to date the collection contains over 600 hand samples of chert and flint, along with a small number of other materials (siliceous limestone, tuff, mudstone). The physical reference collection is housed at the UCD School of Archaeology, University College Dublin and contains the geological hand samples along with the various thin sections of the samples that are used for petrographic analysis. The physical collection is complemented by an online database that is to be used alongside the physical collection, or can be used as a stand-alone resource. This paper provides an overview of the database’s metadata and the processes of data entry and editing, to serve as a reference point for the database and the fieldwork undertaken to date, and to serve as a template for other researchers undertaking similar work on lithic reference collections.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.409
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.047
GPT teacher head0.330
Teacher spread0.283 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

Explore more

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