The CNOC2 Field Galaxy Redshift Survey. I. The Survey and the Catalog for the Patch CNOC 0223+00
Bibliographic record
Abstract
The Canadian Network for Observational Cosmology (CNOC2) Field Galaxy Redshift Survey is a spectroscopic/photometric survey of faint galaxies over 1.5 deg 2 of sky with a nominal spectroscopic limit of R C ∼ 21.5 mag. The primary goals of the survey are to investigate the evolution of galaxy clustering and galaxy populations over the redshift range of ∼0.1-0.6. The survey area contains four widely separated patches on the sky with a total sample of over 6000 redshifts, representing a sampling rate of about 45%. In addition, five-color photometry (in I C , R C , V , B , and U ) for a complete sample of approximately 40,000 galaxies to R C ∼ 23.0 mag is also available. We describe the survey and observational strategies, multiobject spectroscopy mask design procedure, and data reduction techniques for creating the spectroscopic-photometric catalogs. We also discuss the derivations of statistical weights, including corrections for the effects of limited spectral bandwidth, for the redshift sample, which allow it to be used as a complete sample. As the initial release of the survey data, we present the full data set and some statistics for the patch CNOC 0223+00.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".