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Record W4289277588 · doi:10.1117/12.2629231

In-flight performance of the NIRSpec micro shutter array

2022· article· en· W4289277588 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSpace Telescopes and Instrumentation 2022: Optical, Infrared, and Millimeter Wave · 2022
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsnot available
FundersCanadian Space AgencyGoddard Space Flight CenterEuropean Space AgencyNational Aeronautics and Space Administration
KeywordsShutterComputer scienceOpticsPhysics

Abstract

fetched live from OpenAlex

The NIRSpec instrument on the James Webb Space Telescope (JWST) brings the first multi-object spectrograph (MOS) into space, enabled by a programmable Micro Shutter Array (MSA) of ∼250,000 individual apertures. During the 6-month Commissioning period, the MSA performed admirably, completing ∼800 reconfigurations with an average success rate of ∼96% for commanding shutters open in science-like patterns. We show that 82.5% of the unvignetted shutter population is usable for science, with electrical short masking now the primary cause of inoperable apertures. In response, we propose a plan to recheck existing shorts during nominal operations, which is expected to reduce the number of affected shutters. We also present a full assessment of the Failed Open and Failed Closed shutter populations, which both show a marginal increase in line with predictions from ground testing. We suggest an amendment to the Failed Closed shutter flagging scheme to improve flexibility for MSA configuration planning. Overall, the NIRSpec MSA performed very well during Commissioning, and the MOS mode was declared ready for science operations on schedule.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.530

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 science0.0000.000
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 head0.006
GPT teacher head0.185
Teacher spread0.179 · 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