Examining supernova events in Type 1 active galactic nuclei
Bibliographic record
Abstract
ABSTRACT A statistical study of intermediate Palomar Transient Factory supernovae (SNe) in Type 1 active galactic nuclei (AGNs) has shown a major deficit of supernovae around Type 1 AGN host galaxies, with respect to Type 2 AGN hosts. The aim of this work is to test whether there is any preference for Type 1 AGNs to host SN of a specific kind. Through the analysis of SN occurrence and their type (thermonuclear versus core-collapse), we can directly link the type of stars producing the SN events, thus this is an indirect way to study host galaxies in Type 1 AGNs. We examine the detection fractions of SNe, the host galaxies and compare the sample properties to typical host galaxies in the Open Supernova Catalog (OSC). The majority of the host galaxies in the AGN sample are late type, similar to typical galaxies hosting SN within the OSC. The findings are supportive of a deficiency of SNe near Type 1 AGNs, although we cannot with certainty assess the overall detection fractions of SNe in Type 1 AGNs relative to other SN host galaxies. We can state that Type 1 AGN has equal detection fractions of thermonuclear versus core-collapse SNe. However, we note the possibility of a higher detection rate of core-collapse supernovae in Type 1 AGN with insecure AGN classifications.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".