The EXPLORE Project. I. A Deep Search for Transiting Extrasolar Planets
Bibliographic record
Abstract
Planet transit searches promise to be the next breakthrough for extrasolar planet detection and will bring the characterization of short-period planets into a new era. Every transiting planet discovered will have a measured radius, which will provide constraints on planet composition, evolution, and migration history. Together with radial velocity measurements, the absolute mass of every transiting planet will be determined. In this paper we discuss the design considerations of the Extrasolar Planet Occultation Research (EXPLORE) project, a series of transiting planet searches using 4 m class telescopes to continuously monitor a single field of stars in the Galactic plane in each ~2 week observing campaign. We discuss the general factors that determine the efficiency and the number of planets found by a transit search, including time sampling strategy and field selection. The primary goal is to select the most promising planet candidates for radial velocity follow-up observations. We show that with very high photometric precision light curves that have frequent time sampling and at least two detected transits, it is possible to uniquely solve for the main parameters of the eclipsing system (including planet radius), based on several important assumptions about the central star. Together with a measured spectral type for the star, this unique solution for orbital parameters provides a powerful method for ruling out most contaminants to transiting planet candidates. For the EXPLORE project, radial velocity follow-up observations for companion mass determination of the best candidates are done on 8 m class telescopes within 2 or 3 months of the photometric campaigns. This same-season follow-up is made possible by the use of efficient pipelines to produce high-quality light curves within weeks of the observations. We conclude by presenting early results from our first search, EXPLORE I, in which we reached better than 1% rms photometric precision (measured over a full night) on ~37,000 stars with 14.5 ≤ I ≤ 18.2.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".