SN 2023emq: A Flash-ionized Ibn Supernova with Possible C iii Emission
Bibliographic record
Abstract
Abstract SN 2023emq is a fast-evolving transient initially classified as a rare Type Icn supernova (SN), interacting with a H- and He-free circumstellar medium (CSM) around maximum light. Subsequent spectroscopy revealed the unambiguous emergence of narrow He lines, confidently placing SN 2023emq in the more common Type Ibn class. Photometrically, SN 2023emq has several uncommon properties regardless of its class, including its extreme initial decay (faster than >90% of Type Ibn/Icn SNe) and sharp transition in the decline rate from 0.20 to 0.07 mag day −1 at +20 days. The bolometric light curve can be modeled as CSM interaction with 0.32 M ⊙ of ejecta and 0.12 M ⊙ of CSM, with 0.006 M ⊙ of nickel, as expected of fast, interacting SNe. Furthermore, broadband polarimetry at +8.7 days ( P = 0.55% ± 0.30%) is consistent with spherical symmetry. A discovery of a transitional Type Icn/Ibn SN would be unprecedented and would give valuable insights into the nature of mass loss suffered by the progenitor just before death, but we favor an interpretation that SN 2023emq is a Type Ibn SN that exhibited flash-ionized features in the earliest spectrum, as the features are not an exact match with other Type Icn SNe to date. However, the feature at 5700 Å, in the region of C iii and N ii emission, is significantly stronger in SN 2023emq than in the few other flash-ionized Type Ibn SNe, and if it is related to C iii , it possibly implies a continuum of properties between the two classes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".