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Record W4223910775 · doi:10.5539/res.v14n2p47

The Possible 50ft Columns of the Pantheon Lost in Transit

2022· article· en· W4223910775 on OpenAlexvenueno aff
Roger Sik

Bibliographic record

VenueReview of European Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsReignColumn (typography)PluckingOrder (exchange)CulminationActivity-based costingGeologyHistoryArchaeologyLawMathematicsEconomicsGeometryPolitical scienceGeomorphologyPhysics

Abstract

fetched live from OpenAlex

This paper investigates the transportation, labor, quarrying, and time expenses of the 50ft column shafts that possibly were ordered originally for the famous Pantheon in Rome, Italy. The Pantheon currently includes 40ft column shafts though there is evidence showing that it may have been meant for 50ft column shafts as other parts of the monument are set up as so for the insertion of it; for example, as seen when looking at the pediment, there is a second one three meters higher behind it, displaying that the pediment is thought to originally be supported by a larger portico, hence using larger column shafts. A plausible explanation for this is that the 50ft column shafts were the original choice, but were lost in transit while being transported from the quarries in Egypt to Rome. And due to the loss of such expensive labor costing components and likely imperial budget issues, there is an order of 40ft column shafts instead. Assuming that the explanation is true, calculations made using the works by those such as Wilson Jones, Simon Barker, Ben Russel, and Justin Leidwanger are found for comparisons, analyses, and conclusions. Through the evaluations and results, one can interpret the rather great effect the loss had on the entire project and the display of a sense of importance that the Pantheon has during the Hadrian reign and even now.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.005
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.060
GPT teacher head0.266
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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