INFALL/EXPANSION VELOCITIES IN THE LOW-MASS DENSE CORES L492, L694-2, AND L1521F: DEPENDENCE ON POSITION AND MOLECULAR TRACER
Bibliographic record
Abstract
ABSTRACT Although surveys of infall motions in dense cores have been carried out for years, few surveys have focused on mapping infall across cores using multiple spectral-line observations. To fill this gap, we present IRAM 30 m telescope maps of N2H+(1–0), DCO+(2–1), DCO+(3–2), and HCO+(3–2) emission toward two prestellar cores (L492 and L694-2) and one protostellar core (L1521F). We find that the measured infall velocity varies with position across each core and choice of molecular line, likely as a result of radial variations in core chemistry and dynamics. Line-of-sight infall speeds estimated from DCO+(2–1) line profiles can decrease by 40–50 m s−1 when observing at a radial offset pc from the core's dust continuum emission peak. Median infall speeds calculated from all observed positions across a core can also vary by as much as 65 m s−1, depending on the transition. These results show that while single-pointing, single-transition surveys of core infall velocities may be good indicators of whether a core is either contracting or expanding, the magnitude of the velocities they measure are significantly impacted by the choice of molecular line, proximity to the core center, and core evolutionary state.
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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 | 0.001 |
| 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".