THE NEWFIRM MEDIUM-BAND SURVEY: PHOTOMETRIC CATALOGS, REDSHIFTS, AND THE BIMODAL COLOR DISTRIBUTION OF GALAXIES OUT TO<i>z</i>∼ 3
Bibliographic record
Abstract
We present deep near-IR (NIR) medium-bandwidth photometry over the wavelength range 1–1.8 μm in the All-wavelength Extended Groth strip International Survey (AEGIS) and Cosmic Evolution Survey (COSMOS) fields. The observations were carried out using the NOAO Extremely Wide-Field Infrared Imager (NEWFIRM) on the Mayall 4 m Telescope on Kitt Peak as part of the NEWFIRM Medium-Band Survey (NMBS), an NOAO survey program. In this paper, we describe the full details of the observations, data reduction, and photometry for the survey. We also present a public K -selected photometric catalog, along with accurate photometric redshifts. The redshifts are computed with 37 (20) filters in the COSMOS (AEGIS) fields, combining the NIR medium-bandwidth data with existing UV ( Galaxy Evolution Explorer ), visible and NIR (Canada–France–Hawaii Telescope and Subaru Telescope), and mid-IR ( Spitzer /IRAC) imaging. We find excellent agreement with publicly available spectroscopic redshifts, with σ z /(1 + z ) ∼ 1%–2% for ∼4000 galaxies at z = 0–3. The NMBS catalogs contain ∼13,000 galaxies at z > 1.5 with accurate photometric redshifts and rest-frame colors. Due to the increased spectral resolution obtained with the five NIR medium-band filters, the median 68% confidence intervals of the photometric redshifts of both quiescent and star-forming galaxies are a factor of about two times smaller when comparing catalogs with medium-band NIR photometry to NIR broadband photometry. We show evidence for a clear bimodal color distribution between quiescent and star-forming galaxies that persists to z ∼ 3, a higher redshift than has been probed so far.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".