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Record W1975961871 · doi:10.1016/j.crhy.2007.04.007

Adaptive optics for direct detection of extrasolar planets: the Gemini Planet Imager

2007· article· en· W1975961871 on OpenAlexaff
Bruce Macintosh, James Graham, D. M. Palmer, René Doyon, Don Gavel, James Larkin, Rebecca Oppenheimer, Leslie Saddlemyer, J. Kent Wallace, Brian Bauman, Darren Erikson, Lisa Poyneer, Anand Sivaramakrishnan, Rémi Soummer, Jean‐Pierre Véran

Bibliographic record

VenueComptes Rendus Physique · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsHerzberg Institute of AstrophysicsUniversité de Montréal
Fundersnot available
KeywordsCoronagraphPhysicsExoplanetPlanetIntegral field spectrographAdaptive opticsPlanetary systemAstronomyBrightnessInterferometryOpticsAstrophysicsSpectrograph

Abstract

fetched live from OpenAlex

The direct detection of photons emitted or reflected by extrasolar planets, spatially resolved from their parent star, is a major frontier in the study of other solar systems. Direct detection will provide statistical information on planets in 5–50 AU orbits, inaccessible to current Doppler searches, and allow spectral characterization of radius, temperature, surface gravity, and perhaps composition. Achieving this will require new, dedicated, high-contrast instruments. One such system under construction is the Gemini Planet Imager (GPI). This combines a high-order/high-speed adaptive optics system to control wavefront errors from the Earth's atmosphere, an advanced coronagraph to block diffraction, ultrasmooth optics, a precision infrared interferometer to measure and correct systematic errors, and a integral field spectrograph/polarimeter to image and characterize target planetary systems. We predict that GPI will be able to detect planets with brightness less than 10 −7 of their parent star, sufficient to observe warm self-luminous planets around a large population of 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.244
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations30
Published2007
Admission routes1
Has abstractyes

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