Performance of the polarization leakage correction in the PILOT data
Bibliographic record
Abstract
Abstract The Polarized Instrument for Long-wavelength Observation of the Tenuous interstellar medium (PILOT) is a balloon-borne experiment that aims to measure the polarized emission of thermal dust at a wavelength of 240 μm (1.2THz). The PILOT experiment flew from Timmins, Ontario, Canada in 2015 and 2019 and from Alice Springs, Australia in April 2017. The in-flight performance of the instrument during the second flight was described in [1]. In this paper,we present data processing steps that were not presented in [1] and that we have recently implemented to correct for several remaining instrumental effects. The additional data processing concerns corrections related to detector cross-talk and readout circuit memory effects, and leakage from total intensity to polarization. We illustrate the above effects and the performance of our corrections using data obtained during the third flight of PILOT, but the methods used to assess the impact of these effects on the final science-ready data, and our strategies for correcting them will be applied to all PILOT data. We show that the above corrections, and in particular that for the intensity to polarization leakage, which is most critical for accurate polarization measurements with PILOT, are accurate to better than 0.4% as measured on Jupiter during flight#3.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".