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
We introduce MultiPresenter, a novel presentation system designed to work on very large display spaces (multiple displays or physically large high-resolution displays). MultiPresenter allows presenters to organize and present pre-made and dynamic presentations that take advantage of a very large display space accessed from a personal laptop. Presenters can use the extra space to provide long-term persistency of information to the audience. Our design deliberately separates content generation (authoring) from the presentation of content. We focus on supporting presentation flow and a variety of presentation styles, ranging from automated, scripted sequences of pre-made slides to highly dynamic ad-hoc, and non-linear content. By providing smooth transition between these styles, presenters can easily alter the flow of content during a presentation to adapt to an audience or to change emphasis in response to emerging interests. We describe our goals, rationale and the design process, providing a detailed description of the current version of the system, and discuss our experience using it throughout a one-semester first year computer science course.
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.
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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it