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Record W779496055 · doi:10.1016/j.mspro.2015.04.128

Naval Crossfire: A Comparative Analysis of Iron Projectiles from Mid-18th to Early 19th Centuries European Warships

2015· article· en· W779496055 on OpenAlexfundno aff
Nicolás C. Ciarlo, Ariel N. López, Horacio M. De Rosa, Mercedes Pianetti

Bibliographic record

VenueProcedia Materials Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMetallurgy and Cultural Artifacts
Canadian institutionsnot available
FundersInstitute of Aboriginal Peoples HealthChina Aerospace Science and Technology Corporation
KeywordsProjectileCharacterization (materials science)SwiftScanning electron microscopeOrder (exchange)Materials scienceAncient historyHistoryNanotechnologyMetallurgyPhysicsComposite materialBusinessAstrophysics

Abstract

fetched live from OpenAlex

The ordnance of early Modern main maritime powers (i.e. Great Britain, France, and Spain) played an important role in conflicts for supremacy of the seas. Therefore, it was subjected to various innovation processes, in order to improve their efficiency. This study presents the characterization results of an array of iron projectiles recovered from the following sites: 1) the sloop-of-war HMS Swift (1763-1770), 2) the Spanish ship Triunfante (1756-1795), 3) the French ship Bucentaure (1804-1805), and 4) the site Deltebre I (1813). Based on data obtained using Optical Microscopy (OM), Scanning Electron Microscopy (SEM), and Energy Dispersive X-ray Spectrometry (EDXRS), a comparative analysis was performed, in order to clarify the technological differences and similarities that were present in the projectiles used by the mentioned ships.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.116
GPT teacher head0.354
Teacher spread0.238 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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