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Record W3114225911

Acritarcos do Siluriano da Bacia do Amazonas: bioestratigrafia e geocronologia

2005· article· pt· W3114225911 on OpenAlexaboutno aff
Tereza Regina Machado Cardoso

Bibliographic record

VenueArquivos do Museu Nacional (Rio de Janeiro) · 2005
Typearticle
Languagept
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsAcritarchPalynologyGeologyStructural basinAmazon basinAmazon rainforestPaleontologyArchaeologyGeographyPollenEcology
DOInot available

Abstract

fetched live from OpenAlex

This study is based on the palynological investigation of samples from wells 1-AM-1-AM (Autas-Mirim), drilled by PETROBRAS, and SM 1015, SM 1016, SM 1018, SM 1047 and SM 1048, drilled by ELETRONORTE - Centrais Eletricas do Norte do Brasil S.A., in the northern and southern flanks of the Amazon basin. The study area is located in the portion of the Trombetas river comprised between Cachorro and Mapuera rivers, Oriximina town, Para State. The studied section comprises the Pitinga and lower Manacapuru formations of the Trombetas Group. The acritarchs are associated with chitinozoans, chlorophytes, spores and cryptospores. Fifty one species of acritarchs are illustrated and catalogued. The vertical distribution of the most common forms are presented in each analyzed well, discussing the age of acritarchs associations and comparing them with the datings, based on chitinozoans, made Petrobras geologists. The acritarchs species recorded in the Silurian of the Amazon basin, can be correlated with those recorded, e.g., in United States of America, Canada, Saudi Arabia, Spain, Belgium, England, British Isles, Lybia, Poland, Turkey and Sweden (Gotland), indicating the cosmopolitan character

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)0.000
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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.250
Teacher spread0.228 · 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

Citations9
Published2005
Admission routes1
Has abstractyes

Explore more

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