Indicators of Stellar Mass in the Photometric<i>H</i>-band
Bibliographic record
Abstract
Extensive infrared spectral surveys, such as the APOGEE survey in the H -band, are now being conducted, many targeting the Galactic Bulge and recording observations of primarily red giant stars. However, because stars of different masses converge to the red giant region, the masses of single red giant stars are poorly constrained. These surveys are now using spectral resolving powers that are high enough to measure the equivalent widths of individual spectral lines, which are mostly from molecular species. Because other observations can constrain or determine the star's luminosity and radius, we have computed spherical stellar atmospheres for a fixed luminosity and radius but for a range of masses. We then computed the H -band flux spectrum for each model and searched for spectral lines that are sensitive to mass. Our synthetic spectra reveal many lines of CO that become weaker with increasing stellar mass. To explore this, we created a ratio of equivalent widths using a representative, unblended CO line and an unblended OH line that did not vary with mass. We found that this ratio varied about 30% over the mass range from to . We repeated the spectral analysis using spherical model stellar atmospheres computed with a composition solar and found that the ratio displayed a very similar dependence on mass. The presence in the H -band of spectral features sensitive to the masses of red giant stars opens up the potential of constraining more tightly the physical properties of the stars making up the galactic bulge and globular clusters.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".