<i>Herschel</i>-PACS imaging of protostars in the HH 1–2 outflow complex
Bibliographic record
Abstract
We present 70 and 160 μm Herschel science demonstration images of a field in the Orion A molecular cloud that contains the prototypical Herbig-Haro objects HH 1 and 2, obtained with the Photodetector Array Camera and Spectrometer (PACS). These observations demonstrate Herschel's unprecedented ability to study the rich population of protostars in the Orion molecular clouds at the wavelengths where they emit most of their luminosity. The four protostars previously identified by Spitzer 3.6–40 μm imaging and spectroscopy are detected in the 70 μm band, and three are clearly detected at 160 μm. We measure photometry of the protostars in the PACS bands and assemble their spectral energy distributions (SEDs) from 1 to 870 μm with these data, Spitzer spectra and photometry, 2MASS data, and APEX sub-mm data. The SEDs are fit to models generated with radiative transfer codes. From these fits we can constrain the fundamental properties of the protostars. We find luminosities in the range 12–84 and envelope densities spanning over two orders of magnitude. This implies that the four protostars have a wide range of envelope infall rates and evolutionary states: two have dense, infalling envelopes, while the other two have only residual envelopes. We also show the highly irregular and filamentary structure of the cold dust and gas surrounding the protostars as traced at 160 μm.
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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".