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
A successful data collection visualization should satisfy conflicting requirements: unification of diverse data formats, support for serendipity research, support of hierarchical structures, algorithmizability, vast information density, Internet-readiness, etc. The traditional 2D representations of metabolic pathways lack compactness and information density. Virtual reality (VR) has made significant progress in engineering, architectural design, entertainment and communication. Evident advantages of using VR for scientific visualization are subconscious orientation, compromise between overview and detail, memorizing search results, and customization. We experiment with the possibility of using immersive abstract 3D visualizations of metabolic networks. We present the trial Metabolic Network Visualizer (MNV) software, which produces graphical representation of a metabolic network as a VRML (Virtual Reality Modeling Language) world. The entities in the metabolic network are identified as "compartment", "species", "reaction" and "transporter". The properties of the above objects are described using a simple scripting language. The demonstration of the MNV software is available at http://130.239.139.41/sciencevr/mnv/indexview.html.
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 | 0.000 |
| 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