The James Webb Space Telescope Experience: A Lifecycle Approach To Ground Support Equipment
Bibliographic record
Abstract
The James Webb Space Telescope (JWST) developed by the National Aeronautics and Space Administration (NASA), represents a significant undertaking in the study of the early formation of galaxies. Dubbed "NASA's Cosmology Time Machine", JWST is scheduled to launch in 2013. One area Goddard Space Flight Center (GSFC) has responsibility for is the Integrated Science Instrument Module (ISIM) element of JWST, which will integrate the four infrared Science Instruments (Sis) that are currently under development. This represents a considerable challenge, since the various instrument development teams (IDTs) are geographically located in various facilities across the United States, in Europe, and in Canada. A fundamental issue is to manage the risk associated with coordinating the development of the Sis and their associated engineering products with the eventual integration of these independently developed components into ISIM. To this end, the ISIM Team at GSFC has developed a strategy for providing the IDTs with a common set of ground support equipment (GSE) to facilitate their development efforts. This commonality enables the various IDTs to effortlessly share engineering products within the limits imposed by non-technical (i.e., security) constraints.
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 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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".