The Near-Infrared Spectrograph (NIRSpec) on the<i>James Webb</i>Space Telescope
Bibliographic record
Abstract
The near-infrared spectrograph (NIRSpec) on the James Webb Space Telescope (JWST) offers the first opportunity to use integral-field spectroscopy from space at near-infrared wavelengths. More specifically, NIRSpec’s integral-field unit can obtain spectra covering the wavelength range 0.6−5.3 μm for a contiguous 3.1″ × 3.2″ sky area at spectral resolutions of R ≈ 100, 1000, and 2700. In this paper we describe the optical and mechanical design of the NIRSpec integral-field spectroscopy mode, together with its expected performance. We also discuss a few recommended observing strategies, some of which are driven by the fact that NIRSpec is a multipurpose instrument with a number of different observing modes, which are discussed in companion papers. We briefly discuss the data processing steps required to produce wavelength- and flux-calibrated data cubes that contain the spatial and spectral information. Lastly, we mention a few scientific topics that are bound to benefit from this highly innovative capability offered by JWST/NIRSpec.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".