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
This paper introduces Jump, a prototype computer vision-based system that transforms paper-based architectural documents into tangible query interfaces. Specifically, Jump allows a user to obtain additional information related to a given architectural document by framing a portion of the drawing with physical brackets. The framed area appears in a magnified view on a separate display and applies the principle of semantic zooming to determine the appropriate level of detail to show. Filter tokens can be placed on the paper to modify the digital presentation to include information not on the original drawing itself, such as electrical, mechanical, and structural information related to the given space. These filter tokens serve as tangible sliders in that their relative location on the paper controls the degree to which their information is blended with the original document. To address the issue of recognition errors, Jump introduces the notion of a reflection window, or an inset window that serves to reproduce Jump's current interpretation of the visual scene. The system's overall design is informed by a set of in situ studies of architectural technologists and formative evaluations with the same group.
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 | 0.001 |
| Open science | 0.000 | 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 it