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Record W7046522513

Discovering Coptic Churches at Tebtunis

2017· article· en· W7046522513 on OpenAlexaboutno aff

Bibliographic record

VenueResearch Padua Archive (University of Padua) · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsPaintingNaveWhite (mutation)Period (music)Line drawingsArt gallery
DOInot available

Abstract

fetched live from OpenAlex

In 1931 Carlo Anti and Gilbert Bagnani excavated two Coptic churches at Tebtunis in the Fayyum. None of this was published but it has only recently come to light that reports, photos and plans survive in the Istituto Veneto, and that some of the artifacts were sent first to Rome and later transferred to the Turin Museum. In 1933 Bagnani excavated and recorded in a notebook a third church and its attached monastic outbuildings; significantly, the walls of its nave were covered with wall paintings. Above and below these representational scenes were depicted patterns presumably representing hanging tapestries, some of which were copied as watercolors by Gilbert’s wife, Stewart. In 1934 and in 1936, Bagnani had a series of aerial photos taken over the entire site. Through analysis of archival documents, historical photos and artifacts, coming from Anti’s and Bagnani’s campaigns in Egypt (1930-1936), which are now in Italy and Canada, an international team has begun working on the Coptic period in Tebtunis. The team has been able to discover the positions of the three churches, reconstruct their interior design, shed new light on the wall paintings preserved only in black and white photos, and to see the Coptic textile artifacts, now preserved in the Egyptian Museum in Turin, in comparison with the watercolor drawings of Stewart Bagnani.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.002
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.058
GPT teacher head0.315
Teacher spread0.257 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

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