In-flight performance of the NIRSpec micro shutter array
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".