Cosmological inference from combining <i>Planck</i> and ACT cluster counts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT We have adapted the Planck cluster likelihood in such a way that it can be applied to the sample of clusters detected by the Atacama Cosmology Telescope (ACT). Applying it to the Planck sample from 2016 and the ACT sample from 2018, we find, by fixing the cosmology using cosmic microwave background observations and the cluster model adopted by Planck, that the mass bias required by the two are $1-b_{\rm Planck}=0.61\pm 0.03$ and $1-b_{\rm ACT}=0.75\pm 0.06$. These are broadly in agreement but hint that the model could be adapted to reach a better agreement. By normalizing the cluster model using weak lensing observations, we find evidence for either evolution in the cluster model, quantified by the cluster modelling parameter describing redshift dependence $\beta =0.86 \pm 0.07$ using an updated Canadian Cluster Comparison Project (CCCP)-based normalization, or evolution in the cosmological model quantified by the dark energy equation-of-state parameter $w=-0.82 \pm 0.07$.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it