Bibliographic record
Abstract
The James Webb Space Telescope (JWST) is a large aperture, space telescope designed to provide imaging and spectroscopy over the near and mid-infrared from 1.0 μm to 28 μm. JWST is a passively cooled infrared telescope, employing a five layer sunshield to achieve an operating temperature of ~40 K. JWST will be launched to an orbit at L2 aboard an Ariane 5 launcher in 2013. The Goddard Space Flight Center (GSFC) is the lead center for the JWST program and manages the project for NASA. The prime contractor for JWST is Northrop Grumman Aerospace Systems (NGST). JWST is an international partnership with the European Space Agency (ESA), and the Canadian Space Agency (CSA). ESA will contribute the Ariane 5 launch, and a multi-object infrared spectrograph. CSA will contribute the Fine Guidance Sensor (FGS), which includes the Tunable Filter Imager (TFI). A European consortium, in collaboration with the Jet Propulsion Laboratory (JPL), builds the mid-infrared imager (MIRI). In this paper we present an overview of the JWST science program, and discuss recent progress in the development of the observatory. In this paper we will discuss the scientific motivations for JWST, and discuss recent progress in the construction of the observatory, focusing on the telescope and its optics, which have recently completed polishing.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".