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Guia de Acessibilidade para autores de artigos científicos: proposição, desenvolvimento e prospecção

2022· article· pt· W4282914704 on OpenAlexaff
Emilia Christie Picelli Sanches, Juliana Ferreira de OLIVEIRA, Caroline Rodrigues de LIMA, Diovana Mazur Damacena

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldSocial Sciences
TopicScience and Science Education
Canadian institutionsGLS Industries (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Conference -CIDI and 10th Information Design Student Conference -CONGIC. Seeking to expand access to the scientific legacy of the event and taking as a starting point the transposition to the remote modality due to the pandemic, the guide's objective is to make the proceedings digital document accessible to people with different types of disability, promoting inclusive practical actions with the authors. The paper covers the steps of researching, writing the content, designing the guide and stamp, as well as the results obtained from submitted papers. At the end of the paper, learnings and expectations for future events are discussed, aiming to reduce informational barriers and expand the inclusive potential of scientific events.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0110.005
Open science0.0020.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0190.004

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 head0.076
GPT teacher head0.383
Teacher spread0.307 · 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.

Study designNot applicable
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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