The Chandra Source Catalog Normal Galaxy Sample
Bibliographic record
Abstract
Abstract We present the extensive and well-characterized Chandra X-ray Galaxy Catalog (CGC) of 8547 galaxy candidates in the redshift range z ∼ 0.04–0.7, optical luminosity 1010–1011 Lr ⊙, and X-ray luminosity (0.5–7 keV) L X = 2 × 1040–2 × 1043 erg s−1. We estimate a ∼5% false-match fraction and contamination by quasi-stellar objects (QSOs). The CGC was extracted from the Chandra Source Catalog version 2 (CSC2) by cross-correlating with optical and IR all-sky survey data, including the Sloan Digital Sky Survey, Pan-STARRS, DESI Legacy, and Wide-field Infrared Survey Explorer (WISE). Our selection makes use of two main criteria that we have tested on the subsample with optical spectroscopical identification. (1) A joint selection based on X-ray luminosity (L X) and X-ray-to-optical flux ratio (F XO), which recovers 63% of the spectroscopically classified galaxies with a small contamination fraction (7%), which is a significant improvement over methods using L X or F XO alone (<50% recovery). (2) A joint W1–W2 (W12) WISE color and L X selection that proves effective in excluding QSOs and improves our selection by recovering 72% of the spectroscopically classified galaxies and reducing the contamination fraction (4%). Of the CGC, 24% was selected by means of optical spectroscopy; 30% on the basis of L X, F XO, and W12; and 46% by using either the L X–F XO or the L X–W12 selection criteria. We have individually examined the data for galaxies with z < 0.1, which may include more than one CSC2 X-ray source, leading to the exclusion of 110 local galaxies. Our catalog also includes near-IR and UV data and galaxy morphological types.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| 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) | 0.026 | 0.028 |
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".