Galaxy Evolution Probe
Bibliographic record
Abstract
The Galaxy Evolution Probe (GEP) is a concept for a mid- and far-infrared space observatory to measure key properties of large samples of galaxies with large and unbiased surveys. GEP will attempt to achieve zodiacal light and Galactic dust emission photon background-limited observations by utilizing a 6-K, 2.0-m primary mirror and sensitive arrays of kinetic inductance detectors (KIDs). It will have two instrument modules: a 10 to 400 μm hyperspectral imager with spectral resolution R = λ / Δλ ≥ 8 (GEP-I) and a 24 to 193 μm, R = 200 grating spectrometer (GEP-S). GEP-I surveys will identify star-forming galaxies via their thermal dust emission and simultaneously measure redshifts using polycyclic aromatic hydrocarbon emission lines. Galaxy luminosities derived from star formation and nuclear supermassive black hole accretion will be measured for each source, enabling the cosmic star formation history to be measured to much greater precision than previously possible. Using optically thin far-infrared fine-structure lines, surveys with GEP-S will measure the growth of metallicity in the hearts of galaxies over cosmic time and extraplanar gas will be mapped in spiral galaxies in the local universe to investigate feedback processes. The science case and mission architecture designed to meet the science requirements is described, and the KID and readout electronics state of the art and needed developments are described. This paper supersedes the GEP concept study report cited in it by providing new content, including: a summary of recent mid-infrared KID development, a discussion of microlens array fabrication for mid-infrared KIDs, and additional context for galaxy surveys. The reader interested in more technical details may want to consult the concept study report.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.095 | 0.049 |
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".