Census of the Local Universe (CLU) Narrowband Survey. I. Galaxy Catalogs from Preliminary Fields
Bibliographic record
Abstract
Abstract We present the Census of the Local Universe (CLU) narrowband survey to search for emission-line (Hα) galaxies. CLU-Hα has imaged ≈3π of the sky (26,470 deg2) with four narrowband filters that probe a distance out to 200 Mpc. We have obtained spectroscopic follow-up for galaxy candidates in 14 preliminary fields (101.6 deg2) to characterize the limits and completeness of the survey. In these preliminary fields, CLU can identify emission lines down to an Hα flux limit of 10−14 erg s−1 cm−2 at 90% completeness, and recovers 83% (67%) of the Hα flux from cataloged galaxies in our search volume at the Σ = 2.5 (Σ = 5) color excess levels. The contamination from galaxies with no emission lines is 61% (12%) for Σ = 2.5 (Σ = 5). Also, in the regions of overlap between our preliminary fields and previous emission-line surveys, we recover the majority of the galaxies found in previous surveys and identify an additional ≈300 galaxies. In total, we find 90 galaxies with no previous distance information, several of which are interesting objects: 7 blue compact dwarfs, 1 green pea, and a Seyfert galaxy; we also identify a known planetary nebula. These objects show that the CLU-Hα survey can be a discovery machine for objects in our own Galaxy and extreme galaxies out to intermediate redshifts. However, the majority of the CLU-Hα galaxies identified in this work show properties consistent with normal star-forming galaxies. CLU-Hα galaxies with new redshifts will be added to existing galaxy catalogs to focus the search for the electromagnetic counterpart to gravitational wave events.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.001 | 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 | 0.003 |
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".