VennDIS: A JavaFX‐based Venn and Euler diagram software to generate publication quality figures
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
Venn diagrams are graphical representations of the relationships among multiple sets of objects and are often used to illustrate similarities and differences among genomic and proteomic datasets. All currently existing tools for producing Venn diagrams evince one of two traits; they require expertise in specific statistical software packages (such as R), or lack the flexibility required to produce publication-quality figures. We describe a simple tool that addresses both shortcomings, Venn Diagram Interactive Software (VennDIS), a JavaFX-based solution for producing highly customizable, publication-quality Venn, and Euler diagrams of up to five sets. The strengths of VennDIS are its simple graphical user interface and its large array of customization options, including the ability to modify attributes such as font, style and position of the labels, background color, size of the circle/ellipse, and outline color. It is platform independent and provides real-time visualization of figure modifications. The created figures can be saved as XML files for future modification or exported as high-resolution images for direct use in publications.
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 | 0.002 |
| 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) | 0.000 | 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