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Record W1699577428 · doi:10.13092/lo.48.331

Étudier l'écrit SMS: Un objectif du projet sms4science

2011· article· en· W1699577428 on OpenAlex
Louise‐Amélie Cougnon, Thomas François

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLinguistik Online · 2011
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsEston College
Fundersnot available
KeywordsGlobeComputer scienceCorpus linguisticsSociolinguisticsText corpusLinguisticsNatural language processingPsychology

Abstract

fetched live from OpenAlex

This paper details an international project called sms4science that aims to collect text message corpora (hereafter referred to as "SMS corpora") from across the globe for scientific research. The project already has ten participating regions, including Belgium, Réunion, Switzerland and Quebec. This article first presents the initial corpora collected from these four areas (resulting in a combined total of 116'000 text messages) and the accompanying methodology. It then exposes the research possibilities related to it: the corpus-based studies pertain as much to linguistics and sociolinguistics as they do to natural language processing and statistics. A specific statistical study is thus presented here and its possible conclusions outline the differences in SMS practices between regions, notably when you consider abbreviation rate or message length. Finally, the paper delineates the project obstacles and correspondingly proposes fresh perspectives for the ongoing year (2011).

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.246
Teacher spread0.210 · 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