Rapidly Evolving Transients in Archival ZTF Public Alerts
Bibliographic record
Abstract
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 ∼5.2 events per year. Even with a Galactic latitude cut of 20°, eight of the 19 events (∼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 (∼21%) are confirmed extragalactic RETs (one confirmed here for the first time) and the origin of six 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 ≤ 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 KNe 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| 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) | 0.004 | 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".