MétaCan
Menu
Back to cohort
Record W3025220386 · doi:10.3917/i2d.201.0039

Le Service d’aide à la rédaction d’articles (SARA)

2020· article· fr· W3025220386 on OpenAlexaffabout
Prasun Lala, Félix Langevin-Harnois

Bibliographic record

VenueI2D - Information données & documents · 2020
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsHumanitiesArtPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Savoir rédiger et publier un article, préparer une conférence, présenter ses travaux… : ces compétences sont devenues essentielles pour les métiers scientifiques. Or les étudiants des cycles supérieurs éprouvent des difficultés à bien communiquer et se sentent souvent isolés. Pour les aider, quatre professeurs de l’École de technologie supérieure de Montréal, ont lancé en 2013 un Service d’aide à la rédaction d’articles (SARA). Dans cette communauté d’apprentissage, aujourd’hui prise en charge par la Bibliothèque, étudiants, chercheurs et experts, s’entraident, en partageant ressources, activités et expériences.

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)0.021
metaresearch head score (Gemma)0.121
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.707

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.121
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.008
Science and technology studies0.0060.003
Scholarly communication0.0190.010
Open science0.0020.010
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.5040.434

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 head0.177
GPT teacher head0.284
Teacher spread0.107 · 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
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

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueI2D - Information données & documentsSame topicCultural Insights and Digital ImpactsFrench-language works237,207