Water in massive star-forming regions: HIFI observations of W3 IRS5
Bibliographic record
Abstract
We present Herschel observations of the water molecule in the massive star-forming region W3 IRS5. The o-H217O 110-101, p-H218O 111-000, p-H2O 202-111, p-H2O 111-000, o-H2O 221-212, and o-H2O 212-101 lines, covering a frequency range from 552 up to 1669 GHz, have been detected at high spectral resolution with HIFI. The water lines in W3 IRS5 show well-defined high-velocity wings that indicate a clear contribution by outflows. Moreover, the systematically blue-shifted absorption in the H2O lines suggests expansion, presumably driven by the outflow. No infall signatures are detected. The p-H2O 111-000 and o-H2O 212-101 lines show absorption from the cold material (T ~ 10 K) in which the high-mass protostellar envelope is embedded. One-dimensional radiative transfer models are used to estimate water abundances and to further study the kinematics of the region. We show that the emission in the rare isotopologues comes directly from the inner parts of the envelope (T ≳ 100 K) where water ices in the dust mantles evaporate and the gas-phase abundance increases. The resulting jump in the water abundance (with a constant inner abundance of 10-4) is needed to reproduce the o-H217O 110-101 and p-H218O 111-000 spectra in our models. We estimate water abundances of 10-8 to 10-9 in the outer parts of the envelope (T ≲ 100 K). The possibility of two protostellar objects contributing to the emission is discussed.
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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 | 0.001 |
| 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".