Searching for Planetary Transits in Galactic Open Clusters: EXPLORE/OC
Bibliographic record
Abstract
Open clusters potentially provide an ideal environment for the search for transiting extrasolar planets, since they feature a relatively large number of stars of the same known age and metallicity at the same distance. With this motivation, over a dozen open clusters are now being monitored by four different groups. We review the motivations and challenges for open cluster transit surveys for short‐period giant planets. Our photometric monitoring survey of Galactic southern open clusters, the Extrasolar Planet Occultation Research/Open Clusters (EXPLORE/OC) project, was designed with the goals of maximizing the chance of finding and characterizing planets and of providing a statistically valuable astrophysical result in the case of no detections. We use the EXPLORE/OC data from two open clusters, NGC 2660 and NGC 6208, to illustrate some of the largely unrecognized issues facing open cluster surveys, including severe contamination by Galactic field stars (>80%) and the relatively low number of cluster members for which high‐precision photometry can be obtained. We discuss how a careful selection of open cluster targets under a wide range of criteria such as cluster richness, observability, distance, and age can meet the challenges, maximizing chances to detect planet transits. In addition, we present the EXPLORE/OC observing strategy to optimize planet detection, which includes high‐cadence observing and continuously observing individual clusters rather than alternating between targets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".