Reversal of infall in SgrB2(M) revealed by<i>Herschel</i>/HIFI observations of HCN lines at THz frequencies
Bibliographic record
Abstract
Aims. To investigate the accretion and feedback processes in massive star formation, we analyze the shapes of emission lines from hot molecular cores, whose asymmetries trace infall and expansion motions.Methods. The high-mass star forming region SgrB2(M) was observed with Herschel/HIFI (HEXOS key project) in various lines of HCN and its isotopologues, complemented by APEX data. The observations are compared to spherically symmetric, centrally heated models with density power-law gradient and different velocity fields (infall or infall+expansion), using the radiative transfer code RATRAN. Results. The HCN line profiles are asymmetric, with the emission peak shifting from blue to red with increasing J and decreasing line opacity (HCN to H13CN). This is most evident in the HCN 12–11 line at 1062 GHz. These line shapes are reproduced by a model whose velocity field changes from infall in the outer part to expansion in the inner part.Conclusions. The qualitative reproduction of the HCN lines suggests that infall dominates in the colder, outer regions, but expansion dominates in the warmer, inner regions. We are thus witnessing the onset of feedback in massive star formation, starting to reverse the infall and finally disrupting the whole molecular cloud. To obtain our result, the THz lines uniquely covered by HIFI were critically important.
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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 | 0.000 | 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) | 0.001 | 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".