Applying the Gothi Model of Tactile and Haptic Interactions
Bibliographic record
Abstract
This paper discusses the emerging area of tactile and haptic display and some of the breadth of applications of tactile/haptic interactions. While many research studies have provided ergonomic insights into the design of tactile/haptic interactions, the many dimensions and properties of these interactions make it especially difficult to combine the guidance from these individual studies. The GOTHI-05 workshop (Guidelines on Tactile and Haptic Interactions, October 2005) brought researchers together to develop a collection of ergonomic guidance and a framework (the GOTHI model of tactile and haptic interaction (Carter, van Erp, et. al., 2005)) for organizing this guidance. The inaugural meeting of ISO TC159/SC4/WG9 further refined this framework and adopted it as the basis for structuring its new series ISO standards on tactile and haptic interactions. The model itself will be elaborated in ISO 9241-910 Framework for Tactile and Haptic Interactions. The model has already proven useful in identifying and organizing specific guidelines in the first drafts of ISO 9241-920 Guidance on Tactile and Haptic Interaction. The paper discusses the various dimensions and properties of tactile/haptic interactions, identified in an expanded version of GOTHI model and identifies major considerations based on this model for use by developers (and potentially by evaluators) of interfaces that make use of tactile/haptic interactions ISO, 2006).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".