Bibliographic record
Abstract
Abstract Archival [3.6] and [4.5] images are used to identify and characterize variable stars in the Magellanic-type galaxies Holmberg II, NGC 2366, and IC 2574. Using parametric and nonparametric detection methods, 74 confirmed or suspected long-period variables (LPVs) are found. The period distributions of the LPVs in NGC 2366 and IC 2574 are similar. While the period distribution of LPVs in Ho II is uncertain due to small number statistics, there appears to be a deficiency of LPVs with periods between 550 and 650 days when compared with NGC 2366 and IC 2574. The LPVs are diffusely distributed on the sky, and do not follow the underlying light from unresolved stars, as expected if episodes of star formation within the past few hundred megayears have occurred throughout the galaxies, including their outer regions. Distances computed for Ho II and NGC 2366 from the period–luminosity relations (PLRs) agree to within ∼0.1 mag with those based on the tip of the red giant branch (RGB). Efforts to estimate an LPV-based distance modulus for IC 2574 are complicated by the presence of first overtone pulsators among LPVs with periods <600 days, although the PLR at the long-period end is consistent with the distance estimated from the RGB-tip. In addition to the LPVs, 10 candidate sgB[e] or luminous blue variables and two candidate red supergiant variables are also identified. Nine candidate sgB[e] stars that do not show evidence of variability are also identified based on their locations in the color–magnitude diagram.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".