Unveiling Two Deeply Embedded Young Protostars in the S68N Class 0 Protostellar Core with JWST/NIRSpec
Bibliographic record
Abstract
Abstract The near-infrared (NIR) emission of the youngest protostars still needs to be characterized to better understand the evolution of their accretion and ejection activity. We analyze James Webb Space Telescope NIRSpec 1.7–5.3 μm observations of two deeply embedded sources in the S68N protostellar core in Serpens. The North Central source exhibits a highly obscured spectrum (A K ∼ 4.8 mag) that is modeled with a pre-main-sequence photosphere and a hot disk component. The photospheric parameters are consistent with a young, low-mass photosphere, as suggested by the low surface gravity, log g of 1.95 ±0.15 cm s−2. The hot disk suggests that accretion onto the central protostellar embryo is ongoing, although prototypical accretion-tracing emission lines H i are not detected. The South Central source, which is even more embedded (A K ∼ 8 mag; no continuum is detected shortward of 3.6 μm) appears to be driving the large-scale S68N protostellar outflow, and launches a collimated hot molecular jet detected in H2 and CO rovibrational lines. Shock modeling of the H2 (ro)vibrational lines establishes that fast C-type shocks (≥30 km s−1), with high pre-shock density (≥107 cm−3), and strong magnetic field (b ∼ 3–10, where B = b × n H ( cm − 3 ) μ G ) best match the data. The bright CO fundamental line forest suggests energetic excitation, with the contribution of non-LTE effects, i.e., irradiation pumping. Detected OH and CH+ rovibrational lines support this hypothesis. These two Class 0 protostars seem to be in very young evolutionary stages and still have to acquire the bulk of their final stellar masses. These results demonstrate that JWST enables unprecedented diagnostics of these first stages of the protostellar evolutionary phase.
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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".