The MACHO Project LMC Variable Star Inventory. X. The R Coronae Borealis Stars
Bibliographic record
Abstract
We report the discovery of eight new R Coronae Borealis (RCB) stars in the Large Magellanic Cloud (LMC) using the MACHO project photometry database. The discovery of these new stars increases the number of known RCB stars in the LMC to thirteen. We have also discovered four stars similar to the Galactic variable DY Per. These stars decline much more slowly and are cooler than the RCB stars. The absolute luminosities of the Galactic RCB stars are unknown since there is no direct measurement of the distance to any Galactic RCB star. Hence, the importance of the LMC RCB stars. We find a much larger range of absolute magnitudes ( M V = -2.5 to -5 mag) than inferred from the small pre-MACHO sample of LMC RCB stars. It is likely that there is a temperature- M V relationship with the cooler stars being intrinsically fainter. Cool (~5000 K) RCB stars are much more common than previously thought based on the Galactic RCB star sample. Using the fairly complete sample of RCB stars discovered in the MACHO fields, we have estimated the likely number of RCB stars in the Galaxy to be ~3200. The SMC MACHO fields were also searched for RCB stars, but none were found.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.054 |
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".