Research Announcements for the Solar System
Bibliographic record
Abstract
In collaboration with the Legacy Survey of Space and Time (LSST) Solar System Collaboration (SSSC) and the Canadian Astronomy Data Centre (CADC), the Can-Rubin team is developing a new communication platform designed to meet the modern needs of the Solar System research community. Called Research Announcements for the Solar System (RAFTs), this system is intended to streamline the sharing of discoveries, observations, and updates during the fast-moving era of wide-field time-domain surveys like the Vera C. Rubin Observatory LSST. RAFTs are intended to address the unique needs of the Solar System research community in the era of large-scale surveys (such as LSST), providing a streamlined, moderated system for the timely sharing of observational alerts with announcements that are concise, scientifically relevant, and permanently archived. Hosted by the CADC, RAFTs will be freely accessible and easily discoverable with permanent DOIs assigned to each.Each announcement will feature a machine-readable section to facilitate rapid follow-up, and will be integrated with the LSST community forum to encourage further collaborations and engagement. The system will also feature a moderation process to help maintain scientific relevance and quality. The announcements are expected to be brief, relevant, and may be urgent. While urgency is not a requirement for publication, the RAFTs platform will be particularly well-suited for time-sensitive discoveries that benefit from prompt visibility and potential follow-up. The system is designed to be scalable, with the capacity to handle an increased volume of discoveries expected from the LSST. We will present a brief demonstration of the (in development) software interface, highlighting its user-friendly design and functionality for the community.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.261 | 0.213 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".