Spirograph inspired visualization of ecological networks
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
Ecological networks are directed weighted graphs for representing direct and indirect relationships between species in ecosystems. These complex cyclic networks play an important role in understanding an ecosystem's dynamics. In this paper, we present a visualization layout inspired by Spirograph patterns, specifically designed for ecological networks. Our visualization supports both the direct and indirect quantities commonly required in ecological studies. The layout is circular to reflect the containment of the represented ecosystem and to clarify which connections are internal and which are external. In this layout, nodes are arranged along the circumference of a large circle as arcs, and edges are mapped to thorn-like shapes that represent the direction and the weight of the edge. Finally, we illustrate the use of this visualization on several example ecological networks.
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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 | 0.000 | 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 | 0.000 |
| 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