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Record W4385071331 · doi:10.1017/s0068246223000053

THE FALERII NOVI PROJECT

2023· article· en· W4385071331 on OpenAlexaff
Margaret Andrews, Seth Bernard, Emlyn Dodd, Beatrice Fochetti, Stephen Kay, Paolo Liverani, Martin Millett, Frank Vermeulen

Bibliographic record

VenuePapers of the British School at Rome · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicAncient Mediterranean Archaeology and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExpansiveSettlement (finance)ExcavationUrbanismArchaeologyWork (physics)Multinational corporationHuman settlementGeographyHistoryPolitical scienceEngineeringArchitectureLawBusiness

Abstract

fetched live from OpenAlex

The Falerii Novi Project represents a newly formed archaeological initiative to explore the Roman city of Falerii Novi. The project forms a collaboration of the British School at Rome with a multinational team of partner institutions. Thanks to a rich legacy of geophysical work on both the site and its territory, Falerii Novi presents an exceptional opportunity to advance understanding of urbanism in ancient and medieval Italy. The Falerii Novi Project employs a range of methodologies, integrating continued site-scale survey with new campaigns of stratigraphic excavation, archival research and environmental archaeology. The project aims to present a more expansive and holistic urban history of this key Tiber Valley settlement by focusing on long-run socio-economic processes both within Falerii Novi and as they linked the city to its wider landscape.

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)0.004
metaresearch head score (Gemma)0.005
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: Other
Teacher disagreement score0.034
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0050.002
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.009

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 head0.211
Teacher spread0.188 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venuePapers of the British School at RomeSame topicAncient Mediterranean Archaeology and HistoryFrench-language works237,207