Understanding Researchers' Use of a Large, High-Resolution Display Across Disciplines
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A driving force behind the design of increasingly large and high resolution displays (LHRDs) has been the need to support the explosion of data in the natural sciences such as physics, chemistry, and biology. However, our experience with an LHRD accessible to researchers across multiple disciplines has shown that they are useful for a wide range of research activities involving large images and data. \ We conducted in-context, semi-structured interviews with researchers from a variety of disciplines about their experiences using the LHRD with their own data. Notably, it became apparent that the size and resolution of the LHRD supported a multitude of activities related to observation, for which zooming or other enlargement methods on standard resolution screens were not sufficient. The interview findings lead to implications for further research into supporting a broader range of disciplines in using large, high-resolution displays.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it