Bibliographic record
Abstract
When the Universe was around 10 billion years old, it became dominated by dark energy andbegan to accelerate in its expansion. This stage in the expansion history of the Universe iscrucial for distinguishing dark energy models. The Canadian Hydrogen Intensity MappingExperiment (CHIME) is a radio telescope designed to measure the expansion during this periodby mapping the large-scale distribution of neutral hydrogen gas. CHIME will directly detect thehydrogen 21 cm emission redshifted to frequencies between 400 and 800 MHz. Astrophysicalforegrounds are several orders of magnitude brighter than the 21 cm cosmological signal.There is an ongoing effort to understand the instrument to the level of precision required forforeground removal. Measurements of the foregrounds are useful ancillary data products in and of themselves. Todate, the best measurement of the full sky in this frequency regime is the 408 MHz map byHaslam et al. from a survey that was conducted in the 70's. As a drift-scan interferometer,CHIME is uniquely capable of producing maps of the full radio sky on a daily basis. Thesedetailed maps provide valuable astrophysical data at unexplored frequencies. In this work, I willdescribe m-mode formalism, a non-traditional mapmaking strategy in which we take advantage of the instrument's drift-scan design. To validate the method, I show the result of applying it to simulated data. I will present the first CHIME all-sky map at 702 MHz. I discuss the sources of map artifacts and describe the steps that are being taken to mitigate them in forthcoming maps
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".