Binarity of transit host stars
Bibliographic record
Abstract
<i>Context. <i/>Straight-forward derivation of planetary parameters can only be achieved in transiting planetary systems. However, planetary attributes such as radius and mass strongly depend on stellar host parameters. Discovering a transit host star to be multiple leads to a necessary revision of the derived stellar and planetary parameters.<i>Aims. <i/>Based on our observations of 14 transiting exoplanet hosts, we derive parameters of the individual components of three transit host stars (WASP-2, TrES-2, and TrES-4) which we detected to be binaries. Two of these have not been known to be multiple before. Parameters of the corresponding exoplanets are revised.<i>Methods. <i/>High-resolution “Lucky Imaging” with AstraLux at the 2.2 m Calar Alto telescope provided near diffraction limited images in <i>i'<i/> and <i>z'<i/> passbands. These results have been combined with existing planetary data in order to recalibrate planetary attributes.<i>Results. <i/>Despite the faintness (<i>Δ<i/>mag ~ 4) of the discovered stellar companions to TrES-2, TrES-4, and WASP-2, light-curve deduced parameters change by up to more than 1<i>σ<i/>. We discuss a possible relation between binary separation and planetary properties, which – if confirmed – could hint at the influence of binarity on the planet formation process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".