The Toronto Red-Sequence Cluster Survey: First Results
Bibliographic record
Abstract
The Toronto Red-Sequence Cluster Survey (TRCS) is a new galaxy cluster surveydesigned to provide a large sample of optically selected 0.1 < z < 1.4clusters. The planned survey data is 100 square degrees of two color (R and z')imaging, with a 5-sigma depth ~2 mag past M* at z=1. The primary scientificdrivers of the survey are a derivation of Omega_m and sigma_8 (from N(M,z) forclusters) and a study of cluster galaxy evolution with a complete sample. Thispaper gives a brief outline of the TRCS survey parameters and sketches themethods by which we intend to pursue the main scientific goals, including anexplicit calculation of the expected survey completeness limits. Somepreliminary results from the first set of data (~6 deg^2) are also given. Thesepreliminary results provide new examples of rich z~1 clusters, strong clusterlensing, and a possible filament at z~1.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".