Cool, Luminous, and Highly Variable Stars in the Magellanic Clouds. II. Spectroscopic and Environmental Analysis of Thorne–Żytkow Object and Super-AGB Star Candidates
Bibliographic record
Abstract
Abstract In previous work, we identified a population of 38 cool and luminous variable stars in the Magellanic Clouds and examined 11 in detail in order to classify them as either Thorne–Żytkow objects (TŻOs; red supergiants with a neutron star cores) or super-asymptotic giant branch (sAGB) stars (the most massive stars that will not undergo core collapse). This population includes HV 2112, a peculiar star previously considered in other works to be either a TŻO or high-mass asymptotic giant branch (AGB) star. Here we continue this investigation, using the kinematic and radio environments and local star formation history of these stars to place constraints on the age of the progenitor systems and the presence of past supernovae. These stars are not associated with regions of recent star formation, and we find no evidence of past supernovae at their locations. Finally, we also assess the presence of heavy elements and lithium in their spectra compared to red supergiants. We find strong absorption in Li and s-process elements compared to RSGs in most of the sample, consistent with sAGB nucleosynthesis, while HV 2112 shows additional strong lines associated with TŻO nucleosynthesis. Coupled with our previous mass estimates, the results are consistent with the stars being massive (∼4–6.5 M ⊙) or sAGB (∼6.5–12 M ⊙) stars in the thermally pulsing phase, providing crucial observations of the transition between low- and high-mass stellar populations. HV 2112 is more ambiguous; it could either be a maximally massive sAGB star, or a TŻO if the minimum mass for stability extends down to ≲13 M ⊙.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".