Mapping magnetic fields from clouds to cores with PRIMAger
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
High-resolution, wide-area mapping of magnetic field geometries within molecular clouds, including the star-forming filaments and cores within them, is crucial to understanding the role of magnetic fields in the star formation process. We, therefore, propose an unbiased survey of star-forming molecular clouds within 0.5 kpc of the Earth in polarized light with the PRIMAger Polarimetry Imager. We will map magnetic fields over entire molecular clouds at linear resolutions of ∼10−3 to 10−2 pc (∼103 to 104 au) in PRIMAger Bands PPI1 to PPI4, thereby resolving magnetic field structure both within individual star-forming filaments and cores and in the most diffuse regions of molecular clouds. These multiwavelength polarimetric observations will allow us to systematically investigate both the wide range of open questions about the role of magnetic fields in star formation and the evolution of the interstellar medium, and interstellar dust grain properties. The time required to map the area observed by the Herschel Gould Belt Survey (160 deg2) to the cirrus confusion limit in polarized light is 170 h. This will give a 5-σ detection of 20% polarized low-density cirrus emission, with surface brightness in polarized intensity of 1.0 to 2.4 MJy/sr across the PRIMAger bands, and will ensure detection of polarized emission at all higher column densities. This time estimate can be simply scaled up to map magnetic fields in a larger sample of molecular clouds, including more distant regions of higher-mass star formation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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