J-PLUS: Spectral evolution of white dwarfs by PDF analysis
Bibliographic record
Abstract
Aims.We estimated the spectral evolution of white dwarfs with effective temperature using the Javalambre Photometric Local Universe Survey (J-PLUS) second data release (DR2), which provides 12 photometric optical passbands over 2176 deg2. Methods.We analyzed 5926 white dwarfs withr ≤ 19.5 mag in common between a white dwarf catalog defined fromGaiaEDR3 and J-PLUS DR2. We performed a Bayesian analysis by comparing the observed J-PLUS photometry with theoretical models of hydrogen- and helium-dominated atmospheres. We estimated the probability distribution functions for effective temperature (Teff), surface gravity, parallax, and composition; and the probability of having a H-dominated atmosphere (pH) for each source. We applied a prior in parallax, usingGaiaEDR3 measurements as a reference, and derived a self-consistent prior for the atmospheric composition as a function ofTeff. Results.We described the fraction of white dwarfs with a He-dominated atmosphere (fHe) with a linear function of the effective temperature at 5000 < Teff < 30 000 K. We findfHe = 0.24 ± 0.01 atTeff = 10 000 K, a change rate along the cooling sequence of 0.14 ± 0.02 per 10 kK, and a minimum He-dominated fraction of 0.08 ± 0.02 at the high-temperature end. We tested the obtainedpHby comparison with spectroscopic classifications, finding that it is reliable. We estimated the mass distribution for the 351 sources with distanced < 100 pc, massM > 0.45M⊙, andTeff > 6000 K. The result for H-dominated white dwarfs agrees with previous studies, with a dominantM = 0.59M⊙peak and the presence of an excess atM ∼ 0.8M⊙. This high-mass excess is absent in the He-dominated distribution, which presents a single peak. Conclusions.The J-PLUS optical data provide a reliable statistical classification of white dwarfs into H- and He-dominated atmospheres. We find a 21 ± 3% increase in the fraction of He-dominated white dwarfs fromTeff = 20 000 K toTeff = 5000 K.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".