The far-infrared enhanced survey spectrometer (FIRESS) for PRIMA
Bibliographic record
Abstract
FIRESS is the multi-purpose spectrometer proposed for the PRobe far-Infrared Mission for Astrophysics (PRIMA). The sensitive spectrometer on the cold telescope provide factors of 1,000 to 100,000 improvement in spatial-spectral mapping speed relative to Herschel, accessing galaxies across the arc of cosmic history via their dust-immune far-infrared spectral diagnostics. FIRESS covers the 24 to 235 micron range with four slit-fed grating spectrometer modules providing resolving power between 85 and 130. The four slits overlap in pairs so that a complete spectrum of any object of interest is obtained in 2 pointings. For higher-resolving-power studies, a Fourier-transform module (FTM) is inserted into the light path in advance of the grating backends. The FTM serves all four bands and boosts the resolving power up to 4,400 at 112 microns, allowing extraction of the faint HD transition in protoplanetary disks. FIRESS uses four 2016-pixel arrays of kinetic inductance detectors (KIDs) which operate at the astrophysical photon background limit. KID sensitivities for FIRESS have been demonstrated, and environmental qualification of prototype arrays is underway.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".