MAGMO: Mapping the Galactic Magnetic field through OH masers
Bibliographic record
Abstract
Abstract We are undertaking a project (MAGMO) to examine large-scale magnetic fields pervading regions of high-mass star formation. The project will test if the orientations of weak large-scale magnetic fields can be maintained in the contraction (and field amplification) to the high densities encountered in high-mass star forming regions. This will be achieved through correlating targeted observations of ground-state hydroxyl (OH) maser emission towards hundreds of sites of high-mass star formation spread throughout the spiral arms of the Milky Way. Through the Zeeman splitting of the OH maser emission these observations will determine the strength and orientation of the in-situ magnetic field. The completion of the southern hemisphere Methanol Multibeam survey has provided an abundance of targets for ground-state OH maser observations, approximately 1000 sites of high-mass star formation. With this sample, much larger and more homogeneous than previously available, we will have the statistics necessary to outweigh random fluctuations and observe an underlying Galactic magnetic field if it exists. We presented details of the overall progress of the project illustrated by the results of a pilot sample of sources towards the Carina-Sagittarius spiral arm tangent, where a coherent field is implied.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".