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Record W3093715203 · doi:10.1080/00934690.2020.1834255

Practicing Urban Archaeology in a Modern City: The Alessandrino Quarter of Rome

2020· article· en· W3093715203 on OpenAlexaboutno aff
Jan Kindberg Jacobsen, Giovanni Murro, Claudio Parisi Presicce, Rubina Raja, Sine Grove Saxkjær

Bibliographic record

VenueJournal of Field Archaeology · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsnot available
FundersAarhus Universitets ForskningsfondDanmarks GrundforskningsfondAarhus Universitet
KeywordsQuarter (Canadian coin)ArchaeologyExcavationSituatedDocumentationHistoryGeographyComputer science

Abstract

fetched live from OpenAlex

This article describes the documentation according to FAIR principles of the first phase of the excavation of parts of the Alessandrino Quarter—an area of central Rome that has largely remained unexplored, although situated in the center of what is today one of the most visited cities in Europe. Archaeological fieldwork in modern cities presents excavators with a particular set of challenges. Prominent among these is archaeological complexity—the dense and complex stratigraphies, preserving vast amounts of accumulated data, that result from the often continuous transformation of urban space over millennia. While archaeologists readily acknowledge this, they seldom make public the lessons learned from conducting urban archaeological projects in modern contexts. This article seeks to make a contribution specifically in this area.

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)0.002
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.039
GPT teacher head0.267
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

Citations8
Published2020
Admission routes1
Has abstractyes

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