AVALIAÇÃO E MELHORIA DA EXPERIÊNCIA DE USO DO SISTEMA INTEGRADO DE BUSCA DAS BIBLIOTECAS MUNICIPAIS DE SÃO PAULO
Bibliographic record
Abstract
Usabilidade, experiência do usuário, biblioteca O sistema de busca das bibliotecas municipais de São Paulo é uma das primeiras interações entre o usuário e o acervo.Os métodos utilizados nesse trabalho foram: análise heurística, teste de usabilidade, análise de tarefa e mapa de navegação.As propostas de melhorias incluem nova arquitetura de informação e interface. Usability, user experience, libraryThe integrated search system of the municipal libraries of São Paulo is one of the first interactions between the user and the collection of the municipal library.The research methods used were analysis heuristics, usability testing, task analysis and map navigation.The proposals of improvements include new information architecture and new interface.1 Introdução É cada vez mais frequente a preocupação com a experiência de uso de artefatos digitais.Parte disso, por estarmos vivendo um período onde o consumo está sendo reinventado.As pessoas estão se dando conta que não é preciso possuir bens que sejam seus e de uso exclusivo, a economia colaborativa está encontrando cada vez mais adeptos.Serviços de streaming de música e vídeos são os que mais se destacam nesse novo cenário.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".