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Record W4417274732 · doi:10.36660/abc.20250640

Diretriz Brasileira de Dislipidemias e Prevenção da Aterosclerose – 2025

2025· article· en· W4417274732 on OpenAlexaff
Fabiana Hanna Rached, Márcio H. Miname, Viviane Zorzanelli Rocha, André Zimerman, Fernando Yue Cesena, Andrei C. Spósito, Raúl D. Santos, Paulo Eduardo Ballvé Behr, Henrique Tria Bianco, Renato Jorge Alves, André Árpád Faludi, Elaine dos Reis Coutinho, Francisco Antônio Helfenstein Fonseca, Luiz Sérgio Fernandes de Carvalho, Adriana Bertolami, Aloísio M. Rocha, Ana Paula Marte Chacra, Antônio Carlos Palandri Chagas, Bruno Caramelli, Carísi Anne Polanczyk, Carlos Eduardo dos Santos Ferreira, Carlos Serrano, Daniel Branco de Araújo, Emílio Hideyuki Moriguchi, Fausto J. Pinto, Humberto Graner Moreira, Isabela de Carlos Back Giuliano, José Rocha Faria‐Neto, Kleisson Antônio Pontes Maia, Marcelo Chiara Bertolami, Marcelo Heitor Vieira Assad, Maria Cristina de Oliveira Izar, Mauricio Alves Barreto, Natasha Slhessarenko Fraife Barreto, Pedro Gabriel Melo de Barros e Silva, Raul Cavalcante Maranhão, Sérgio Kaiser, Valéria A. Machado, José Francisco Kerr Saraiva

Bibliographic record

VenueArquivos Brasileiros de Cardiologia · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Health in Brazil
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsTriglycerides bloodLdl cholesterol

Abstract

fetched live from OpenAlex

que, em última análise, deve determinar o tratamento apropriado para seus pacientes.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.258
Threshold uncertainty score0.513

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.050
GPT teacher head0.390
Teacher spread0.341 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractno

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