The MACHO Project Large Magellanic Cloud Variable Star Inventory. XII. Three Cepheid Variables in Eclipsing Binaries
Bibliographic record
Abstract
We present a method for solving the light curve of an eclipsing binary system that contains a Cepheid variable as one of its components as well as the solutions for three eclipsing Cepheids in the Large Magellanic Cloud (LMC). A geometric model is constructed in which the component stars are assumed to be spherical and on circular orbits. The emergent system flux is computed as a function of time, with the intrinsic variations in temperature and radius of the Cepheid treated self-consistently. Fitting the adopted model to photometric observations, incorporating data from multiple bandpasses, yields a single parameter set best describing the system. This method is applied to three eclipsing Cepheid systems from the MACHO project LMC database: MACHO 6.6454.5, 78.6338.24, and 81.8997.87. A best-fit value is obtained for each system's orbital period and inclination and for the relative radius, color, and limb-darkening coefficients of each star. Pulsation periods and parameterizations of the intrinsic color variations of the Cepheids are also obtained, and the amplitude of the radial pulsation of each Cepheid is measured directly. The system 6.6454.5 is found to contain a 4.97 day Cepheid, which cannot be definitely classified as type I or type II, with an unexpectedly brighter companion. The system 78.6338.24 consists of a 17.7 day, W Virginis class type II Cepheid with a smaller, dimmer companion. The system 81.8997.87 contains an intermediate-mass, 2.03 day overtone Cepheid with a dimmer, red giant secondary.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".