Low-redshift Type Ia Supernova from the LSQ/LCO Collaboration
Bibliographic record
Abstract
Abstract This paper is the data release of a new sample of 140 type Ia supernovae (SNe Ia) from the LaSilla-QUEST/Las Cumbres Observatory (LCO) collaboration. The discovery of the supernovae came from the LaSilla-QUEST variability survey, the ASASSN survey, as well as smaller low redshift supernova surveys. All of the supernovae in this sample were spectroscopically identified as SNe Ia using spectra from the PESSTO survey using the 3.5 m NTT telescope at LaSilla and spectra from the LCO 2 m Faulkes telescopes. The light-curves were obtained from a rapid cadence photometric follow up of the supernovae with the 9 LCO 1 m telescopes located at various observatories around the globe. Reference images of the host galaxies were taken approximately a year after the supernova have faded to allow precise galaxy background subtraction from the supernova magnitudes. The supernovae in this sample were discovered over a seven year period from 2012 October to 2019 June, and the last galaxy reference images were taken before 2020 June.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".