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Entrevista com Hércules Tolêdo Corrêa

2019· article· pt· W2990384335 on OpenAlexaboutno aff
Gláucia Maria dos Santos Jorge

Bibliographic record

VenueDebates em educação · 2019
Typearticle
Languagept
FieldArts and Humanities
TopicLinguistics and Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Entrevista realizada pela professora Gláucia Jorge com professor Hércules Tolêdo Corrêa é Doutor em Educação - área Educação e Linguagem – pela Universidade Federal de Minas Gerais - UFMG (2002); Mestre em Letras: Estudos Linguísticos pela UFMG (1996); e graduado em Letras/Português pela UFMG (1989). Fez estágios científicos avançados de pós-doutoramento (Pós-Doc) na York Univeristy, em Toronto, no Canadá, no segundo semestre de 2017 e no primeiro semestre de 2018, e na Universidade do Minho, em Braga, Portugal, no primeiro semestre de 2007. O tema da entrevista foi sua experiencia de pos doutorado na York Univeristy, em Toronto, no Canadá.

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)0.022
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0060.004
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0260.007

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 head0.040
GPT teacher head0.298
Teacher spread0.258 · 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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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