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Record W4322766783 · doi:10.1007/s11457-023-09351-w

Sheathing and Pay Techniques in the Boa Vista 1 Ship (Lisbon, Portugal)

2023· article· en· W4322766783 on OpenAlexfundno aff
Gonçalo Lopes, Francisco Petrucci‐Fonseca

Bibliographic record

VenueJournal of Maritime Archaeology · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
FundersUniversidade de LisboaFundação para a Ciência e a TecnologiaFederation for the Humanities and Social Sciences
KeywordsKeelHullShipbuildingArchaeologyTowerNaval architectureEngineeringGeographyMarine engineering

Abstract

fetched live from OpenAlex

Abstract Between September 2012 and February 2013, archaeological excavations carried out in the riverside area of Lisbon (Portugal) revealed the remains of two wooden ships: Boa Vista 1 (BV1) and Boa Vista 2 (BV2), both dating from the late seventeenth or early eighteenth century. BV1 ship consists of scattered hull timbers which were damaged and out of their original positions. Some of the ship’s hull features are common in the Mediterranean like a composite keel with butt joints and hook scarfs in the connection between floors and futtocks, while others are well-known Iberian shipbuilding features like the transition between the keel and the sternpost being made through a single piece, the heel. A unique feature was a layer of animal hair between the sheathing and the hull planking. This paper focuses mainly on the study of wooden sheathing, including but not limited to the analysis of its conventional “architectural signatures”. The latest results concerning animal hair identification will also be presented and discussed, showing the added value of multidisciplinary approaches in archaeology.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.244
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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