Bibliographic record
Abstract
Half a century after measurement of the lunar brightness temperature for preparations of the moon landing, Canadian Hydrogen Intensity Mapping Experiment (CHIME) provides improved instrumentation and a more sophisticated method for the same measurement. Such measurement also helps our understanding of CHIME itself and extends its limit, such as better calibration of antenna beam patterns and understanding of the artifacts within CHIME data. Previous research in 1950s has provided multiple data points with lunar brightness temperatures from 230 to 240 Kelvin between 100MHz and 1000MHz. However, a recent measurement performed by Murchison Widefield Array (MWA) indicates a much lower value of the lunar brightness temperature around 180 Kelvin at 150 MHz. Given that the CHIME band is also in low frequencies, a series of measurements can be performed between 400MHz and 800MHz to test the result from MWA which can potentially reject 1950s’ results and enhance our knowledge about lunar brightness temperature in low frequencies. This research is aimed to measure the lunar brightness temperature within the CHIME band from 400MHz to 800MHz. To measure the lunar brightness temperature from CHIME’s visibility data, Fringestop was performed. Subsequently, an averaged background intensity was measured and subtracted from the intensity obtained after Fringestop. Rayleigh Jeans Law was used to finalize the calculation of the lunar brightness temperature. There is inconsistency in my result. Between the two measured lunar brightness temperature values at different times and frequencies, one agrees with the 1950s measurement while the other agrees with the data measured by MWA in 2017. Nevertheless, this study helps to pave the foundation of lunar brightness temperature measurement with CHIME. More future measurements can be performed and averaged with improved 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".