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Record W2941897344 · doi:10.1002/nsg.12046

GPR Investigations at St John's Co‐Cathedral in Valletta

2019· article· en· W2941897344 on OpenAlexaff
Raffaele Persico, Sebastiano D’Amico, Loredana Matera, Emanuele Colica, Cynthia de Giorgio, Adriana Alescio, Charles V. Sammut, Pauline Galea

Bibliographic record

VenueNear Surface Geophysics · 2019
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsNaveGround-penetrating radarGeologyArchaeologyMosaicRadarHistoryEngineering

Abstract

fetched live from OpenAlex

ABSTRACT The Cathedral of St John in Valetta, Malta, represents a unique monument of historical importance. In this paper, we present the results of a detailed ground penetrating radar campaign performed in this Cathedral. The campaign was aimed at investigating the distribution of buried tombs under the mosaic floor of the main nave and of the lateral chapels of the Co‐Cathedral. The floor of the church shows a continuity of grave inscriptions in the main nave as well as in all lateral chapels. It was suspected, based on available historical documents, that only a part of the present‐day inscriptions corresponds to the original sepultures or tombs. The ground penetrating radar results presented here further highlight this conjecture and offer additional information regarding this important monument.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.239
Teacher spread0.228 · 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

Citations29
Published2019
Admission routes1
Has abstractyes

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