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Record W4399215792 · doi:10.1080/14614103.2023.2299909

Water Reservoirs in North-Western <i>Hispania</i> Roman Gold Mining: Technology, Chronology and Paleoenvironmental Evolution

2024· article· en· W4399215792 on OpenAlexfundno aff
Almudena Orejas Saco del Valle, Brais X. Currás Refojos, Damián Romero Perona, Sebastián Pérez Díaz, Juan Luis Pecharromán, José Antonio López Sáez, F. Javier Sánchez-Palencia

Bibliographic record

VenueEnvironmental Archaeology · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
FundersWestern UniversityImperial Oil Limited
KeywordsChronologyArchaeologyGeologyGold miningGeographyAncient historyHistoryChemistry

Abstract

fetched live from OpenAlex

Water reservoirs located on the mining fronts were essential for the operation of Roman gold mining. They served purposes such as the extraction and washing of gold deposits, and the final disposal of waste. The history of a Roman gold mine is intricately linked to its hydraulic network. Therefore, dating the construction, usage, and abandonment layers of water reservoirs enables us to comprehend the evolution of mining operations. In this paper, we present a methodological approach consisting of the opening of archaeological sondages in the water reservoirs to understand their stratigraphy and operating phases, together with sampling to obtain chronological and pollen information. We present the work carried out in four case studies located in various mining areas in the northwest of the Iberian Peninsula. Results indicate that water reservoirs serve as paleoenvironmental archives, facilitating the chronological unravelling of mining operations and the landscape reconstruction from the period immediately preceding the onset of mining operations to their abandonment. Results also have highlighting some of the challenges when interpreting radiocarbon results. We conclude that the archaeological analysis of hydraulic mining infrastructure is an effective methodology for understanding the evolution of mining landscapes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.005
GPT teacher head0.174
Teacher spread0.168 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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