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Record W7015590472

TM/Landsat-5 and SAR image digital processing applied to identify salt affected soils zones in the Baixada de Sousa, State of the ParaÃba, Brazil

2001· article· en· W7015590472 on OpenAlexfundno aff

Bibliographic record

VenueBiblioteca Digital da Memória Científica do INPE (National Institute for Space Research) · 2001
Typearticle
Languageen
FieldEngineering
TopicSynthetic Aperture Radar (SAR) Applications and Techniques
Canadian institutionsnot available
FundersUniversidade Federal da ParaíbaUniversity of Manitoba
KeywordsSoil waterAridHydrology (agriculture)Image processingDigital image processingDigital image analysisDigital imageDigital elevation modelSynthetic aperture radar
DOInot available

Abstract

fetched live from OpenAlex

This paper describes the use of TM/Landsat-5 and Radarsat digital image processing to study salt affected soils zones in arid and semi-arid regions, Baixada de Sousa, in the State of the Paraíba, Brazil has been selected as a test area.

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)0.000
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 score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

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

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 head0.030
GPT teacher head0.335
Teacher spread0.305 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueBiblioteca Digital da Memória Científica do INPE (National Institute for Space Research)Same topicSynthetic Aperture Radar (SAR) Applications and TechniquesFrench-language works237,207