Cosmology in front of the background: studying the growth of structure at CMB wavelengths
Bibliographic record
Abstract
Canada has thriving communities in CMB (cosmic microwave background) studies, cosmology and submillimetre (submm) astronomy, with involvement in many facilities that featured prominently in previous Astronomy Long Range Plans. The standard cosmological model continues to be well fit using a small number of parameters. No one expects this model to be complete and so we need to continue to challenge it with data; moreover, it does not explain how galaxies and other structures form. So, how do we improve the precision of our understanding of structure formation within this model? Wavelengths from the microwave to the submm will be particularly fruitful for answering this question. That's because, in addition to the CMB anisotropies, there are other signals that can be extracted from large maps at these wavelengths - particularly the cosmic infrared and submm backgrounds, the thermal and kinetic Sunyaev-Zeldovich effects, and CMB lensing. Such signals carry a wealth of information about the cosmological model, as well as how dust, gas and star-formation evolve within dark-matter halos. Cross-correlations between these signals and those coming from the radio, optical and X-ray surveys, will provide even more information. Canadians are already members of teams for several related facilities and are working to be involved in others. In order for Canada to be fully engaged in exploiting the detailed information coming from these cosmological signatures, it is crucial that we find the resources to participate competitively in a combination of projects currently being planned. Examples include CMB-S4, CCAT-prime, AtLAST, a new camera for JCMT, balloon projects such as BFORE and a future ambitious CMB satellite.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".