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Record W7120744849

Caderno de Anais da XV Semana de Letras do CPAN

2024· book· pt· W7120744849 on OpenAlexaboutno aff
Carlos Eduardo de Araujo Placido

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2024
Typebook
Languagept
FieldSocial Sciences
TopicRural and Ethnic Education
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaResilience (materials science)Context (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

O Caderno de Anais da XV Semana de Letras do CPAN compila os trabalhos mais relevantes que foram apresentados na seção Comunicação Oral do principal evento de divulgação científica da área dos Estudos Linguísticos e Literários do Câmpus Pantanal (CPAN). Esses trabalhos foram selecionados por meio de pareceristas especializados de Letras e revisados pelos seus próprios autores extensivamente. O evento acadêmico-científico SeleCpan (Semana de Letras do CPAN) é o evento mais antigo e tradicional da região fronteiriça Brasil-Bolívia. Ele vem ocorrendo de forma intermitente desde a criação/funcionamento do curso de Letras Português/Espanhol há mais de 14 anos. Entretanto, o curso de Letras Português/Inglês do CPAN existe desde 1968. Ele foi o primeiro curso instalado nessa região de fronteira. Por conseguinte, o Caderno de Anais da XV Semana de Letras do CPAN propõe divulgar gratuitamente os trabalhos científicos e os trabalhos de conclusão de curso (TCC) de maior destaque do nosso alunado. Isso tanto à comunidade interna quanto à comunidade externa da Universidade Federal de Mato Grosso do Sul (UFMS).

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)0.001
metaresearch head score (Gemma)0.003
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 score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.003

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 head0.041
GPT teacher head0.297
Teacher spread0.256 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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