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Record W2319045974 · doi:10.1017/s0068245400016828

Ceramic fabric analysis and survey archaeology: the Sphakia Survey

2003· article· en· W2319045974 on OpenAlex
Jennifer Moody, Harriet Lewis Robinson, Jane E. Francis, Lucia Nixon, Lucy Wilson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Annual of the British School at Athens · 2003
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTerminologyPotteryCeramicArchaeologyTurkishComputer scienceMaterials scienceGeographyComposite materialLinguistics

Abstract

fetched live from OpenAlex

Macroscopic Fabric Analysis, the systematic study and description of ceramic fabrics with the aid of a handlens and other simple equipment, has grown in importance along with systematic archaeological survey. Microscopic Fabric Analysis, or ceramic petrology, is better known, but more expensive and time-consuming. Using examples drawn from Sphakia Survey material, the authors show that Macroscopic Fabric Analysis of large pottery collections with a high proportion of coarse ware sherds, when combined with targeted microscopic analysis, provides detailed, reliable information on crucial topics such as chronology, in this case from FN/EM I–Turkish; function (cooking, transport, storage, and beehives); and regional interaction. The authors also discuss issues connected with publication, including the use of electronic publications such as the Sphakia Survey website, and the rigorous comparison of individual fabrics, and they make a case for adopting standard ceramic terminology.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.224
Teacher spread0.198 · 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