Stray light modeling of the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM)
Bibliographic record
Abstract
This paper describes an integrated stray light model of each Science Instrument (SI) in the Integrated Science Instrument Module (ISIM) of the James Webb Space Telescope (JWST) and the Optical Telescope Element Simulator (OSIM), the light source used to characterize the performance of ISIM in cryogenic-vacuum tests at the Goddard Space Flight Center (GSFC). We present three cases where this stray light model was integral to solving questions that arose during the testing campaign – 1) ghosting and coherent diffraction from hardware surfaces in the Near Infrared Imager and Slitless Spectrograph (NIRISS) GR700XD grism mode, 2) ghost spots in the Near Infrared Camera (NIRCam) GRISM modes, and 3) scattering from knife edges of the NIRCam focal plane array masks.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".