Research report. Interacting with huge hierarchies: beyond cone trees
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
The paper describes an implementation of a tool for visualizing and interacting with huge information hierarchies, and some preliminary empirical evaluation of the tool's efficacy. Existing systems for visualizing huge hierarchies using cone trees "break down" once the hierarchy to be displayed exceeds roughly 1000 nodes, due to increasing visual clutter. The paper describes a system called fsviz which visualizes arbitrarily large hierarchies while retaining user control. This is accomplished by augmenting cone trees with several graphical and interaction techniques: usage-based filtering, animated zooming, hand-coupled rotation, fish-eye zooming, coalescing of distant nodes, texturing, effective use of colour for depth cueing, and the applications of dynamic queries. The fsviz system also improves upon earlier cone tree visualization systems through a more elaborate node layout algorithm. This algorithm enhances the usefulness of cone tree visualization for large hierarchies by all but eliminating clutter.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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