A luminous stellar outburst during a long-lasting eruptive phase first, and then SN IIn 2018cnf
Bibliographic record
Abstract
We present the results of the monitoring campaign of the Type IIn supernova (SN) 2018cnf (a.k.a. ASASSN-18mr). It was discovered about ten days before the maximum light (on MJD = 58 293.4 ± 5.7 in the V band, with MV = −18.13 ± 0.15 mag). The multiband light curves show an immediate post-peak decline with some minor luminosity fluctuations, followed by a flattening starting about 40 days after maximum. The early spectra are relatively blue and show narrow Balmer lines with P Cygni profiles. Additionally, Fe II, O I, He I, and Ca II are detected. The spectra show little evolution with time and with intermediate-width features becoming progressively more prominent, indicating stronger interaction of the SN ejecta with the circumstellar medium. The inspection of archival images from the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) survey has revealed a variable source at the SN position with a brightest detection in December 2015 at Mr = −14.66 ± 0.17 mag. This was likely an eruptive phase from the massive progenitor star that started from at least mid-2011, and that produced the circumstellar environment within which the star exploded as a Type IIn SN. The overall properties of SN 2018cnf closely resemble those of transients such as SN 2009ip. This similarity favours a massive hypergiant, perhaps a luminous blue variable, as progenitor for SN 2018cnf.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".