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Desenvolvimento de metodologia para aplicar técnicas do paleomagnetismo em anomalias magnetométricas em crosta continental: aplicação a anomalias brasileiras

2009· article· pt· W1997260240 on OpenAlexaff
Renato Cordani

Bibliographic record

VenueBrazilian Journal of Geophysics · 2009
Typearticle
Languagept
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsContinental (Canada)
Fundersnot available
KeywordsGeologyGeomorphologyClimatology

Abstract

fetched live from OpenAlex

RESUMO.O presente trabalho apresenta uma nova metodologia multidisciplinar que capaz de estimar a idade de uma rocha-fonte a partir de sua anomalia magntica apenas, usando dados magnetomtricos areos ou terrestres.Parte-se de anomalias magnticas preferencialmente isoladas, e cuja componente remanescente seja provvel em func o do formato da anomalia.A partir dela calculamos a direc o total da magnetizac o e estudamos as possveis razes entre as componentes induzidas e remanescentes.Posteriormente, determinamos o segmento de reta que congrega todos os paleoplos virtuais possveis, e finalmente relacionamos esse segmento de reta curva de Deriva Polar Aparente da placa tectnica na qual a anomalia est hospedada.Aplicamos diversos testes de consistncia na metodologia criada, usando exemplos sintticos e reais, nas placas Sulamericana e Australiana.Finalmente, aplicamos a metodologia em cinco (5) conhecidas anomalias do territ rio brasileiro, produzidas por complexos alcalinos de idade Mesozica.As idades aparentes obtidas atravs da metodologia criada em trs das anomalias cujas idades radiomtricas so bem conhecidas -Tapira, Arax e Juqui -so similares s idades publicadas.As idades aparentes obtidas atravs das outras duas anomalias cuja idade radiomtrica desconhecida -Registro e Pariquerac u -foram coerentes relativamente ao contexto geolgico.Espera-se que a aplicac o da metodologia ora criada possa contribuir para o conhecimento geolgico das rochas

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.293
Teacher spread0.262 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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