Erratum: “Multiwavelength Mass Comparisons of the<i>z</i>∼ 0.3 CNOC Cluster Sample” (ApJ, 652, 232 [2006])
Bibliographic record
Abstract
In our original paper there was a miscalculation in the determination of central gas densities for that sample, which we correct here.We also report a processing error in the exposure map for MS 1512.4+3647 and supply a correction factor for its surface brightness normalization and background.The code which was used to determine cluster central densities contained an error such that it did not account for a (1 þ z) 3 cosmological dimming factor, derived from a combination of cosmological distance and time dilation corrections.Subsequently, all central densities, gas masses, and gas mass fractions reported in the paper should be scaled up by a factor of (1 þ z) 3/2 .An error also occurred in the production of the exposure map for MS 1512.4+3647, which caused the best-fit surface brightness normalization and background for that cluster to be reduced by a factor of 8 (all other -model values remain unaffected).Therefore, the SB normalization and background of MS 1512.4+3647should be multiplied by this factor, while its central gas density, gas mass, and gas mass fraction should be multiplied by ffiffi ffi 8 p (in addition to the cosmological factor mentioned above).Table A1 contains updated values for central densities, gas masses, and gas mass fractions, along with 90% confidence intervals.Using these values, we obtain a weighted mean gas mass fraction for the sample, f gas (R 200 ) ¼ 0:136 AE 0:004 h À3/2 70 , resulting in m ¼ 0:28 AE 0:01, a value consistent with WMAP 3 year results ( D. N. Spergel et al., ApJS, 170, 377 [2007]).We emphasize that these corrections do not otherwise affect our results.In particular, our main conclusion remains valid, e.g., our finding that there is very good agreement between X-ray, dynamical, and weak-lensing cluster mass estimation methods.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.051 | 0.029 |
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".