The 6C** sample of steep-spectrum radio sources – I. Radio data, near-infrared imaging and optical spectroscopy
Bibliographic record
Abstract
We present basic observational data on the 6C * * sample.This is a new sample of radio sources drawn from the 151-MHz 6C survey, which was filtered with radio criteria chosen to optimize the chances of finding radio galaxies at z > 4. The filtering criteria are a steep-spectral index and a small angular size.The final sample consists of 68 sources from a region of sky covering 0.421 sr.We present Very Large Array radio maps, and the results of K-band imaging and optical spectroscopy.Near-infrared counterparts are identified for 66 of the 68 sources, down to a 3σ limiting magnitude of K ∼ 22 mag in a 3-arcsec aperture.Eight of these identifications are spatially compact, implying an unresolved nuclear source.The K-magnitude distribution peaks at a median K ≈ 18.7 mag, and is found to be statistically indistinguishable from that of the similarly selected 6C * sample, implying that the redshift distribution could extend to z 4.Redshifts determined from spectroscopy are available for 22 (32 per cent) of the sources, over the range of 0.2 z 3.3.We measure 15 of these, whereas the other seven were previously known.Six sources are at z > 2.5.Four sources show broad emission lines in their spectra and are classified as quasars.Three of these show also an unresolved K-band identification.11 sources fail to show any distinctive emission and/or absorption features in their spectra.We suggest that these could be (i) in the so-called 'redshift desert' region of 1.2 < z < 1.8 or (ii) at a greater redshift, but feature weak emission-line spectra.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".