Projected distances to host galaxy reduce SNIa dispersion
Bibliographic record
Abstract
We use multiband imagery data from the Sloan digital sky survey to measure projected distances of 302 supernova Type Ia (SNIa) from the centre of their host galaxies, normalized to the galaxy’s brightness scale length, with a Bayesian approach. We test the hypothesis that SNIae further away from the centre of their host galaxy are less subject to dust contamination (as the dust column density in their environment is smaller) and/or come from a more homogeneous environment. Using the Mann–Whitney U test, we find a statistically significant difference in the observed colour correction distribution between SNIae that are near and those that are far from the centre of their host. The local p-value is 3 × 10−3, which is significant at the 5 per cent level after look-elsewhere effect correction. We estimate the residual scatter of the two sub-groups to be 0.073 ± 0.018 for the far SNIae, compared to 0.114 ± 0.009 for the near SNIae – an improvement of 30 per cent, albeit with a low-statistical significance of 2σ. This confirms the importance of host galaxy properties in correctly interpreting SNIa observations for cosmological inference.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".