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Record W4399670533 · doi:10.1117/12.3018045

SPIDERS: a pathfinder 4th generation planet imager

2024· article· en· W4399670533 on OpenAlexaff
William R. Thompson, Adam B. Johnson, Olivier Lardière, Christian Marois, Darryl Gamroth, Christopher R. Mann, Angus Bews, Garima Singh, Tim Hardy, Jean‐Pierre Véran, Maaike van Kooten, Joeleff Fitzsimmons, Mamadou N’Diaye, Frédéric Grandmont, Suresh Sivanandam, Simon Thibault, Wolfgang Heidrich, Qiang Fu, Krzysztof Caputa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsUniversity of TorontoABB (Canada)Herzberg Institute of AstrophysicsUniversity of VictoriaNational Research Council Canada
Fundersnot available
KeywordsPathfinderComputer scienceAstrobiologyPlanetAstronomyPhysicsWorld Wide Web

Abstract

fetched live from OpenAlex

The Subaru Pathfinder Instrument for Detecting Exoplanets and Recovering Spectra (SPIDERS) has been built from the ground-up to demonstrate the fast-atmospheric self-coherent camera technique on-sky for the first time. This technique uses a common-path interferometer to measure and suppress speckles in real-time to build a dark hole, and to enable hyperspectral coherent differential imaging post-processing. These promise more than a hundred times improvement in sensitivity to young giant planets and debris disks around bright stars compared with previous, speckle-limited instruments. We will present SPIDERS, its laboratory performance on post-AO residuals, and an update on SPIDERS’ commissioning at Subaru.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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.

Opus teacher head0.014
GPT teacher head0.205
Teacher spread0.190 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations1
Published2024
Admission routes1
Has abstractyes

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