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Record W4365452774 · doi:10.3989/arq.arqt.2023.003

Urban dining rooms in Lusitania: a metrological and morphological approach

2023· article· en· W4365452774 on OpenAlexfundno aff
Filipe Sousa, Catarina Felício

Bibliographic record

VenueArqueología de la Arquitectura · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeological and Historical Studies
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaFederation for the Humanities and Social Sciences
KeywordsHomogeneousHierarchyCharacter (mathematics)GeographySizingPoint (geometry)Set (abstract data type)Computer scienceEconomic geographyMathematicsArtVisual artsGeometryCombinatoricsPolitical science

Abstract

fetched live from OpenAlex

This study aims to characterise the urban dining rooms located in the province of Lusitania from a metrological and morphological point of view. The studied examples were identified in the cities of Conimbriga (Condeixa-a-Velha), Capera (Cáparra), Augusta Emerita (Mérida), and Mirobriga (Santiago do Cacém) and were built between the 1st and the 3rd century CE. The conducted analyses demonstrated the existence of a certain hierarchy in room dimensions, with widths being more homogeneous. This led to the definition of four size clusters, that have a more heterogeneous set of lengths associated, suggesting greater importance of room width, possibly related to the placement of the couches. The existence of relatively standardised size clusters, as well as the presence of several dining rooms in the same house, suggest a relationship between size and functional character, as well as the existence of established rules for the sizing of certain spaces.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.231
Teacher spread0.207 · 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
Published2023
Admission routes1
Has abstractyes

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