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Modèle du lieu en design d’interaction

2018· article· fr· W2318866418 on OpenAlexaff
Éric Kavanagh, Jacynthe Roberge

Bibliographic record

VenueInterfaces numériques · 2018
Typearticle
Languagefr
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Siège des activités humaines, le lieu est d’une grande importance en design d’interaction. Investi de sens, de valeurs, de conventions et d’attentes, le lieu se définit au-delà de sa nature physique. C’est aussi une réalité complexe, aux dimensions multiples, qui exerce une réelle influence sur nos interactions et nos comportements. Pour plusieurs raisons, le lieu demeure une notion très ardue à appréhender en design d’interaction. Cette difficulté prive trop souvent les interfaces d’une réelle convivialité, caractéristique déterminante de la réussite d’une relation entre humain et interface. Nous posons une réflexion sur les principaux lieux de l’interaction humain-interface et proposons un modèle des éléments à considérer pour la prise en compte d’un lieu particulièrement riche et complexe : le lieu psychologique.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.007
Scholarly communication0.0070.008
Open science0.0020.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0140.003

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 head0.042
GPT teacher head0.270
Teacher spread0.228 · 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 designTheoretical or conceptual
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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