MétaCan
Menu
Back to cohort

LOW COST TECHNIQUES FOR THE DIGITAL SURVEY OF A MINOAN ARCHITECTURE IN THE ARCHEOLOGICAL SITE OF PHAISTOS (CRETE)

2019· article· en· W2990083001 on OpenAlexaboutno aff
D. Aiello, Francesca Buscemi, Graziana D’Agostino, Mariateresa Galizia, Pietro Militello, Cettina Santagati

Bibliographic record

Venue˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsnot available
FundersDipartimento Ingegneria Civile e Architettura, Università di CataniaUniversità di Catania
KeywordsPhotogrammetryArchaeologyArchitectureHEROQuarter (Canadian coin)Pipeline (software)Action (physics)HistoryVisual artsArtGeographyComputer scienceRemote sensingArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract. The paper shows the results of an experimentation on the use of low cost tools such as action cameras for the photogrammetric surveying of relevant archaeological sites characterized by the presence of narrow and complex rooms. The archaeological site chosen for this experimentation is the South-Western Quarter, also known as Quartiere Levi, of the Minoan Palace of Phaistos (Crete), one of only two cases of buildings surviving up to the third floor in the Aegean world. The research foresaw the setting up of a pipeline aimed at obtaining a complete scaled, photorealistic and navigable 3D model, with a considerable economy in terms of work time and number of photographs. For this purpose, many efforts have been paid on solving all the issues related to the complexity of the site and on comparing the performances of traditional (Canon EOS 70D) and action (GoPro Black Hero 6) cameras as well as of two of the current most used software in the field.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.249
Teacher spread0.227 · 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 designBench or experimental
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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venue˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesSame topic3D Surveying and Cultural HeritageFrench-language works237,207