Cryogenic testing of detector alignment of the Fine Guidance Sensor for the James Webb Space Telescope
Bibliographic record
Abstract
The development of the James Webb Space Telescope (JWST) is an international collaboration led by NASA in partnership with the European Space Agency and the Canadian Space Agency (CSA). The Canadian contribution to the mission is the Fine Guidance Sensor (FGS). The FGS-Guider images two fields of view onto two detectors. For testing, Optical Ground Support Equipment telescopes are used to simulate the image from the Observatory's Optical Telescope Element. The FGS Engineering Test Unit (ETU) comprises 2 functioning Guider channels: one fully functional channel with a Teledyne H2RG HgCdTe 5 micron cutoff detector, and another with an H2RG multiplexer in place of a detector. This paper reports on the results of cryogenic vacuum testing of the alignment of the final ETU instrument configuration. Images at ambient (from the H2RG multiplexer) and at cryo (from detector and H2RG multiplexer) were analysed to determine best focus and FGS field of view at cryogenic temperatures. The ETU test results for best focus, tip/tilt of focal planes, field of view location and size are well matched to the budgets and predictions and meet requirements for the FGS-Guider.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".