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Record W4312617850 · doi:10.14393/rbcv67n7-49200

AVALIAÇÃO DA ACURÁCIA DOS ORTOMOSAICOS E MODELOS DIGITAIS DO TERRENO GERADOS PELO ΜVANT/DNPM

2019· article· en· W4312617850 on OpenAlexaff
Cristiano Alves Da Silva, Michael Vandesteen Silva Souto, Cynthia Romariz Duarte, Cristina Prando Bicho, José Antônio Beltrão Sabadia

Bibliographic record

VenueRevista Brasileira de Cartografia · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsProfessional Engineers Ontario
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

This present paper aims to demonstrate the evaluation of the accuracy of orthomosaics and Digital Terrain Models(DTM) generated by the Unmanned Aerial Vehicle (UAV) developed by the University of Brasilia (UnB) in partnershipwith the National Department of Mineral Production (DNPM). This study evaluated the orthomosaic and the MDTfrom a pile of laminated limestone exploitation tailings in the Santana do Cariri municipality, state of Ceará, processedin three diff erent situations: (1) without the use of ground control points; (2) using 4 ground control points, located inbuildings around the stack; and (3) using10 ground control points, pre-signaled on the surface of the tailing pile. The assessment of accuracy was performed from the trend analysis and accuracy of the models, and the results classifi edaccording to the Standard Cartographic Accuracy of Digital Cartographic Products (PEC-PCD). The results showedthat the evaluated products are precision and reliability compatible with those obtained by conventional aerial photogrammetry, if properly oriented by ground control points.

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)0.001
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 score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.003

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 head0.021
GPT teacher head0.242
Teacher spread0.221 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueRevista Brasileira de CartografiaSame topic3D Surveying and Cultural HeritageFrench-language works237,207