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Record W3007175854 · doi:10.5753/wpietf.2017.3610

Analisando a participação do Brasil e dos demais países da América Latina nos encontros do IETF

2017· article· pt· W3007175854 on OpenAlexaff
Julião Braga, Patrícia Takako Endo, Marcelo Santos, Jéferson Campos Nobre, Leylane Graziele Ferreira da Silva, Gleyson Rhuan Nascimento Campos, Nizam Omar

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldComputer Science
TopicInformation Science and Libraries
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPolitical scienceLatin Americans

Abstract

fetched live from OpenAlex

Este artigo aborda a participação de brasileiros nos encontros do IETF comparando com outros países da América Latina e Caribe. Adicionalmente ele descreve as iniciativas de participação no desenvolvimento de documentos e os movimentos que disponibilizam recursos para financiar tais participações. Descreve as iniciativas brasileiras que estimulam a participação e recomenda outras que levadas a cabo no Brasil e em outros países da América Latina e Caribe aumentarão a presença de mais voluntários.

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)0.005
metaresearch head score (Gemma)0.014
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 score0.155
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.010
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.078
GPT teacher head0.329
Teacher spread0.251 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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