Spectroscopic confirmation of high-redshift supernovae with the ESO VLT
Bibliographic record
Abstract
We present VLT FORS1 and FORS2 spectra of 39 candidate high-redshift supernovae that were discovered as part of a cosmological study using type Ia supernovae (SNe Ia) over a wide range of redshifts. From the spectra alone, 20 candidates are spectrally classified as SNe Ia with redshifts ranging from to . Of the remaining 19 candidates, 1 might be a type II supernova and 11 exhibit broad supernova-like spectral features and/or have supernova-like light curves. The candidates were discovered in 8 separate ground-based searches. In those searches in which SNe Ia at were targeted, over 80% of the observed candidates were spectrally classified as SNe Ia. In those searches in which SNe Ia with were targeted, 4 candidates with were spectrally classified as SNe Ia and later followed with ground and space based observatories. We present the spectra of all candidates, including those that could not be spectrally classified as supernova.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".