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Cartas Náuticas com Modelos SEP: Evolução Histórica, e Perspectivas para Hidrografia Brasileira

2020· article· en· W3118206568 on OpenAlexaboutno aff
Felipe Rodrigues Santana, Cláudia Pereira Krueger, Tulio Alves Santana, Guilherme Antonio Gomes do Nascimento, Aluízio Maciel Oliveira

Bibliographic record

VenueRevista Brasileira de Cartografia · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHumanitiesGeomorphologyGeologyArt

Abstract

fetched live from OpenAlex

Advances in high-precision GNSS techniques have allowed the reduction of vertical uncertainties in bathymetric surveys, with a better determination of the heave, the dynamic draft and the reduction of co-tidal errors. However, it is necessary to determine a separation model (SEP) between the Chart Datum and the reference ellipsoid. This article will present a historical evolution on the development of SEP models in the world across seven countries: the United States, Canada, Netherlands, Saudi Arabia, Colombia, England and Brazil. Research from foreign countries shows uncertainties in SEP models ranging from 6.6 cm to 22.6 cm in relation to the ITRF. In the case of Brazil, a pioneering study for the SEP of Guanabara Bay is described, where an average difference of 2.5 cm was found with a standard deviation of 5.1 cm between the surface generated with the traditional reduction method and by GPS-tide. For national coverage, the Alt-Bat project is presented, which provides the use of the geoid as a vertical reference for hydrodynamic models. As for the prospects, there is a virtuous cycle for port development: investment in environmental data, provides greater accuracy of SEP models and less uncertainty of surveys, providing greater draft, possibility of increased cargo flow in ports and more resources for investment. SEP models are fundamental for the gathering of information from different vertical references, providing safe navigation and management of coastal process.

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), 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 score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.259
Teacher spread0.208 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

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