SN 2017ivv: two years of evolution of a transitional Type II supernova
Bibliographic record
Abstract
ABSTRACT We present the photometric and spectroscopic evolution of the Type II supernova (SN II) SN 2017ivv (also known as ASASSN-17qp). Located in an extremely faint galaxy (Mr = −10.3 mag), SN 2017ivv shows an unprecedented evolution during the 2 yr of observations. At early times, the light curve shows a fast rise (∼6−8 d) to a peak of ${\it M}^{\rm max}_{g}= -17.84$ mag, followed by a very rapid decline of 7.94 ± 0.48 mag per 100 d in the V band. The extensive photometric coverage at late phases shows that the radioactive tail has two slopes, one steeper than that expected from the decay of 56Co (between 100 and 350 d), and another slower (after 450 d), probably produced by an additional energy source. From the bolometric light curve, we estimated that the amount of ejected 56Ni is ∼0.059 ± 0.003 M⊙. The nebular spectra of SN 2017ivv show a remarkable transformation that allows the evolution to be split into three phases: (1) Hα strong phase (<200 d); (2) Hα weak phase (between 200 and 350 d); and (3) Hα broad phase (>500 d). We find that the nebular analysis favours a binary progenitor and an asymmetric explosion. Finally, comparing the nebular spectra of SN 2017ivv to models suggests a progenitor with a zero-age main-sequence mass of 15–17 M⊙.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".