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A diachronic multi-source approach to the study of a historical landscape in Central-Western Europe: the Blies Survey Project

2023· article· en· W4387497897 on OpenAlexaff
Sonia Antonelli, Jean‐Pierre Petit, Andreas Stinsky, Chiara Casolino, Simona D'Arcangelo, Peter Haupt, Marco Moderato, Serge Occhietti, Vincent Ollive, Dominic Rieth, Sebastian Smith

Bibliographic record

VenueGroma Documenting archaeology · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicAncient and Medieval Archaeology Studies
Canadian institutionsUniversité du Québec à Montréal
FundersMinistero degli Affari Esteri e della Cooperazione InternazionaleMinisterul Educaţiei Naţionale
KeywordsPrehistoryContext (archaeology)ArchaeologySettlement (finance)GeographyHuman settlementNatural (archaeology)

Abstract

fetched live from OpenAlex

Blies Survey Project (BSP) is an international cross-border research project aimed at reconstructing the historical landscapes around the ancient settlement of Bliesbruck-Reinheim, within a radius of 12 km. The research project is focused on a region located between the eastern part of the Moselle department in France and the southern part of Saarland in Germany, between two river valleys (namely the Blies and the Sarre) characterized by a long-lasting human occupation, from prehistory to the present. The geomorphological context and the natural environment of the riverbanks and the low hills have been significantly interrelated with settlement patterns and human occupation.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0120.013
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.000
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 head0.085
GPT teacher head0.286
Teacher spread0.201 · 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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