Combination of tactile devices for data analytics
Bibliographic record
Abstract
Although ubiquitous data analysis is a promising approach, analyzing data in spreadsheets on tablets is a tedious task due to the limited size of the display and tactile vocabulary. In this article, we present the design and evaluation of new interaction techniques based on the combination of a tablet containing the data and a smartphone used as a mediator between the user and the tablet. To do this, we propose to use stacking gestures, i. e. to place a smartphone on top of a tablet. Stacking is an inexpensive, easy to implement, efficient and effective way to improve the analysis of data on tablets, increasing the vocabulary and broadening the display surface by using smartphones that are always available. We first explore stacking-based solutions to delimit the possible interaction vocabulary and present the manufacture of a conductive shell for smartphones. Then, we propose new techniques based on stacking to perform data analysis of a spreadsheet, i.e. the creation of pivot tables and their manipulation. We evaluate our stacking techniques against the tactile interactions provided by current mobile spreadsheet applications. Our studies reveal that some of our interaction techniques are 30% faster than touch to create pivot tables. Bien que l'analyse ubiquitaire de données soit une approche prometteuse, l'analyse des données dans des tableurs sur des tablettes est une tâche fastidieuse en raison de la taille limitée de l'affichage et du vocabulaire tactile. Dans cet article, nous présentons la conception et l'évaluation de nouvelles techniques d'interaction reposant sur la combinaison d'une tablette contenant les données et d'un smartphone utilisé comme médiateur entre l'utilisateur et la tablette. Pour ce faire, nous proposons d'utiliser des gestes de "stacking", c'est-à-dire de poser une arrête d'un smartphone sur l'écran de la tablette. Le stacking est un moyen peu coûteux, facile à mettre en oeuvre, efficace, et basé sur l'utilisation des smartphones toujours disponibles pour améliorer l'analyse des données sur des tablettes, en augmentant le vocabulaire utilisé et en élargissant la surface d'affichage. Nous explorons d'abord des solutions basées sur le stacking pour délimiter le vocabulaire d'interaction possible et présenter la fabrication d'une coque conductive pour smartphone. Ensuite, nous proposons de nouvelles techniques basées sur le stacking pour réaliser l'analyse de données d'un tableur, c'est-à-dire la création de tableaux croisés dynamiques et leur manipulation. Nous évaluons nos techniques de stacking par rapport aux interactions tactiles fournies par les applications de tableur mobiles actuelles. Nos études révèlent que certaines de nos techniques d'interaction sont 30% plus rapides que le toucher pour créer des tableaux croisés dynamiques.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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; a candidate call from one teacher head, 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".