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Record W2175371367 · doi:10.1086/427982

Searching for Planetary Transits in Galactic Open Clusters: EXPLORE/OC

2005· article· en· W2175371367 on OpenAlexaff
Kaspar von Braun, Brian L. Lee, Sara Seager, H. K. C. Yee, G. Mallén-Ornelas, Michael D. Gladders

Bibliographic record

VenuePublications of the Astronomical Society of the Pacific · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsOpen clusterPhysicsPlanetExoplanetMetallicityAstronomyPhotometry (optics)StarsStar clusterTerrestrial planetAstrophysicsAstrobiology

Abstract

fetched live from OpenAlex

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 (EXPLORE/OC) of Galactic southern open clusters was designed with the goals of maximizing the chance of finding and characterizing planets, and of providing for 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 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.266
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2005
Admission routes1
Has abstractyes

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