A high-energy catalogue of Galactic supernova remnants and pulsar wind nebulae
Bibliographic record
Abstract
Abstract Motivated by the wealth of past, existing, and upcoming X-ray and gamma-ray missions, we have developed the first public database of high-energy observations of all known Galactic Supernova Remnants (SNRs): http://www.physics.umanitoba.ca/snr/SNRcat . The catalogue links to, and complements, other existing related catalogues, including Dave Green's radio SNRs catalogue. We here highlight the features of the high-energy catalogue, including allowing users to filter or sort data for various purposes. The catalogue is currently targeted to Galactic SNR observations with X-ray and gamma-ray missions, and is timely with the upcoming launch of X-ray missions (including Astro-H in 2014). We are currently developing the existing database to include an up-to-date Pulsar Wind Nebulae (PWNe)-dedicated webpage, with the goal to provide a global view of PWNe and their associated neutron stars/pulsars. This extensive database will be useful to both theorists to apply their models or design numerical simulations, and to observers to plan future observations or design new instruments. We welcome input and feedback from the SNR/PWN/neutron stars community.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.013 |
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".