AuroraX - an open data platform for auroral science
Bibliographic record
Abstract
AuroraX (https://aurorax.space) is an open data platform for auroral science. The project's primary objective is to enable mining and exploration of existing and future auroral data, enabling key science and enhancing the benefits of the world's investment in auroral instrumentation. This is accomplished with the development of key systems/standards for uniform metadata generation and search, image content analysis, interfaces to leading international tools, and a community involvement that includes more than 80% of the world's data providers. The AuroraX platform significantly lowers the barrier of entry to the global network of auroral data, and provides the foundation for efficiency and inter-operability of existing auroral instrument networks and data streams. Use of cutting-edge web frameworks, enhanced metadata, and discovery tools we allow for rapid access and utilization of auroral data by the space physics and citizen science communities. Enabled by key international partnerships and Canada's leading role in auroral instrumentation, AuroraX hopes to fundamentally change the data landscape for auroral science.
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".