Information Visualization User Testing guided by BASSTEP Approach to Design: Preliminary Results
Bibliographic record
Abstract
Reports of information visualization user testing show they are performed when the design is mature and no longer able to change significantly. This communication presents preliminary results from a novel user evaluation method which controls for novelty and learning effects, and is applicable early in the design process.Les résultats de l’expérience de visualisation de l’information des usagers montrent ce qui se produit lorsque le projet est arrivé à maturité et n’est plus susceptible de changer de manière significative. Cette communication présente les résultats préliminaires d’une nouvelle méthode d’évaluation de l’usager. Cette méthode contrôle la nouveauté et l’effet d’apprentissage, et peut être appliquée à un stade précoce du processus de conception.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.009 | 0.040 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".