Rapidly Evolving Transients in Archival ZTF Public Alerts
Bibliographic record
Abstract
We search the archival Zwicky Transient Facility public survey for rapidly evolving transient (RET) candidates based on well-defined criteria between 2018 May and 2021 December. The search yielded 19 bona-fide RET candidates, corresponding to a discovery rate of $\sim 5.2$ events per year. Even with a Galactic latitude cut of $20^\circ$, 8 of the 19 events ($\sim 42$%) are Galactic, including one with a light-curve shape closely resembling that of the GW170817 kilonova (KN). An additional event is a nova in M31. Four out of the 19 events ($\sim 21$%) are confirmed extragalactic RETs (one confirmed here for the first time) and the origin of 6 additional events cannot be determined. We did not find any extragalactic events resembling the GW170817 KN, from which we obtain an upper limit on the volumetric rate of GW170817-like KNe of $R \le$ 2400 Gpc$^{-3}$ yr$^{-1}$ (95% confidence). These results can be used for quantifying contaminants to RET searches in transient alert streams, specifically when searching for kilonovae independently of gravitational-wave and gamma-ray-burst triggers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| 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) | 0.007 | 0.002 |
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".