Parkes observations for project P1219 semester 2025APRS_15
Bibliographic record
Abstract
Magnetic fields are fundamental in regulating star formation and the evolution of molecular clouds. Zeeman splitting offers a unique method to directly measure line-of-sight magnetic field strengths in interstellar environments, from the diffuse ISM to dense cores. Observations of HI and OH absorption toward pulsars provide an unprecedented opportunity to measure magnetic fields with high precision, benefiting from pulsars' small angular sizes and reliable Stokes V spectra unaffected by instrumental effects. Our recent tentative Zeeman splitting detections in OH absorption toward PSR J1644-4559 with Parkes reveal magnetic field strengths that suggest magnetically subcritical states, where magnetic pressure counteracts gravity. This challenges conventional theories of subcritical cold neutral medium (CNM) transitioning to supercritical star-forming molecular clouds, emphasizing the need for detailed investigation. We propose a continuation of Zeeman splitting studies through high-sensitivity OH and HI absorption observations of pulsars PSR J1644-4559, J1721-3532, and J1852+0031 using Parkes. By employing an innovative phase-resolved spectral technique and extending integration times, we aim to enhance Zeeman detection sensitivity and study magnetic field transitions in the CNM and quiescent molecular clouds. This work will refine our understanding of subcritical-to-supercritical transitions in star formation, establish pulsar absorption as a robust probe of interstellar magnetic fields, and advance observational techniques critical to star formation studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.078 | 0.031 |
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".