EXPLORE/OC: A photometric search for transiting extrasolar planets in southern open clusters
Bibliographic record
Abstract
Our eclipsing binary sample is large enough to offer a statistical view on the evolution of the fraction of eclipsing binaries in open clusters. Using our cluster contact binaries, we find evidence that the fraction of contact binaries increases on a timescale of Gyr, consistent with previous work. Extending those previous results to detached binaries, we find that detached binaries in clusters are destroyed on Gyr timescales. Pooling our detached binary detections from both clusters and the field, we find no support for the hypothesis that the binary mass ratio distribution is peaked towards equal masses. In each cluster field, we find of order one transit-like variable, and dozens of eclipsing binary stars and pulsators. This number of planet candidates is in line with the expected frequency of planet occurrence derived from other planet searches. Extrasolar Planets Occultation Research in Open Clusters (EXPLORE/OC) is a monitoring survey of eight Southern open clusters, designed to detect transits of close-in extrasolar giant planets. In total, the survey produced a sample of approximately 32000 stars with 2--10 mmag photometric precision (rms). For stars both in clusters and the Galactic field, we discriminate between planet transits and other sources that vary with amplitudes of a few percent by combining this excellent precision with high time-sampling (1000--2000 measurements per star, spread over three weeks). The survey employs special techniques to measure and characterize the tens of thousands of sources. The data reduction pipeline incorporates neighbour subtraction and a generalized aperture photometry approach for mitigation of common observational systematic errors. We evaluate distances and spectral types for our sources by spectral energy distribution fitting. Armed with distance estimates, we are able to assign robust cluster membership probabilities to our sources.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".