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Record W2003931391 · doi:10.5380/rf.v35i3.5188

QUANTIFICAÇÃO DE MACRONUTRIENTES EM FLORESTA OMBRÓFILA MISTA MONTANA UTILIZANDO DADOS DE CAMPO E DADOS OBTIDOS A PARTIR DE IMAGENS DO SATÉLITE IKONOS II

2005· article· pt· W2003931391 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFLORESTA · 2005
Typearticle
Languagept
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsCentre de Santé et de Services Sociaux Cavendish
Fundersnot available
KeywordsPhysicsForestryEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

O objetivo deste trabalho foi desenvolver uma metodologia para estimar os macronutrientes (N, P, K, S, Ca e Mg) presentes em uma floresta nativa, utilizando dados espectrais provenientes de satélite de alta resolução, IKONOS II, e dados de campo. As amostras de biomassa foram coletadas em 20 parcelas distribuídas em vários estágios sucessionais da floresta. Os teores de nutrientes em cada espécie foram obtidos em análises de laboratório, e a quantificação por parcela foi feita multiplicando-se esses teores pela biomassa seca. Por meio de análise estatística, relacionaram-se as quantidades de nutrientes nas parcelas com os dados obtidos nas imagens de satélite. Os valores de reflectância nas bandas MS-1, MS-2, MS-3, MS-4 e os índices de vegetação NDVI, SAVI e Razão de Bandas entraram no modelo como variáveis independentes, e os nutrientes, como dependentes. Foram geradas equações alométricas, o que permitiu a quantificação e o mapeamento dos nutrientes para a área.

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.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.013
GPT teacher head0.247
Teacher spread0.235 · 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