Mass‐losing Semiregular Variable Stars in Baade’s Windows
Bibliographic record
Abstract
By cross-correlating the results of two recent large-scale surveys, the general properties of a well-defined sample of semiregular variable stars have been determined. ISOGAL mid-infrared photometry (7 and 15 μm) and MACHO V and R light curves are assembled for approximately 300 stars in the Baade's windows of low extinction toward the Galactic bulge. These stars are mainly giants of late M spectral type, evolving along the asymptotic giant branch (AGB). They are found to possess a wide and continuous distribution of pulsation periods and to obey an approximate log P - M bol relation or set of such relations. Approximate mass-loss rates in the range of ~1 × 10 -8 to 5 × 10 -7 M ☉ yr -1 are derived from ISOGAL mid-infrared photometry and models of stellar spectra adjusted for the presence of optically thin circumstellar silicate dust. Mass-loss rates depend on luminosity and pulsation period. Some stars lose mass as rapidly as short-period Mira variables but do not show Mira-like amplitudes. A period of 70 days or longer is a necessary but not sufficient condition for mass loss to occur. For AGB stars in the mass-loss ranges that we observe, the functional dependence of mass-loss rate on temperature and luminosity can be expressed as ∝ T α L β , where α = -8.80 and β = +1.74 , in agreement with recent theoretical predictions. If we include our mass-loss rates with a sample of extreme mass-losing AGB stars in the Large Magellanic Cloud and ignore T as a variable, we get the general result for AGB stars that ∝ L 2.7 , valid for AGB stars with 10 -8 < < 10 -4 M ☉ yr -1 .
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".