BSN. II. The First Light Curve Study of Eight Total Eclipsing Contact Binary Stars with Shallow Fillout Factors
Bibliographic record
Abstract
Abstract This study provides the first comprehensive analysis of eight total-eclipse W Ursae Majoris-type contact binary systems. Ground-based photometric multiband observations were conducted at a Mexican observatory, and new times of minima were extracted. The O–C analysis reveals that four of our target binaries exhibit a long-term increase in their orbital periods, while the others show a long-term decrease in their orbital periods. We analyzed the light curves using the PHOEBE Python code and BSN application. Among the target systems, two required the inclusion of a cold starspot on one of the components to achieve an adequate fit. The light curve analysis revealed that the target systems exhibit a shallow fillout factor. Absolute parameters were estimated using the Gaia DR3 parallax and astrophysics equations. Considering the effective temperatures and component masses, each system was classified as either the A- or W-subtype. The stellar evolution of the systems was represented through the mass–radius and mass–luminosity diagrams. Additionally, we calculated the initial masses of the companion stars and the total mass lost for each target system.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".