MOLECULAR OUTFLOWS DRIVEN BY LOW-MASS PROTOSTARS. I. CORRECTING FOR UNDERESTIMATES WHEN MEASURING OUTFLOW MASSES AND DYNAMICAL PROPERTIES
Bibliographic record
Abstract
We present a survey of 28 molecular outflows driven by low-mass protostars, all of which are sufficiently isolated spatially and/or kinematically to fully separate into individual outflows. Using a combination of new and archival data from several single-dish telescopes, 17 outflows are mapped in 12 CO (2–1) and 17 are mapped in 12 CO (3–2), with 6 mapped in both transitions. For each outflow, we calculate and tabulate the mass ( M flow ), momentum ( P flow ), kinetic energy ( E flow ), mechanical luminosity ( L flow ), and force ( F flow ) assuming optically thin emission in LTE at an excitation temperature, T ex , of 50 K. We show that all of the calculated properties are underestimated when calculated under these assumptions. Taken together, the effects of opacity, outflow emission at low velocities confused with ambient cloud emission, and emission below the sensitivities of the observations increase outflow masses and dynamical properties by an order of magnitude, on average, and factors of 50–90 in the most extreme cases. Different (and non-uniform) excitation temperatures, inclination effects, and dissociation of molecular gas will all work to further increase outflow properties. Molecular outflows are thus almost certainly more massive and energetic than commonly reported. Additionally, outflow properties are lower, on average, by almost an order of magnitude when calculated from the 12 CO (3–2) maps compared to the 12 CO (2–1) maps, even after accounting for different opacities, map sensitivities, and possible excitation temperature variations. It has recently been argued in the literature that the 12 CO (3–2) line is subthermally excited in outflows, and our results support this finding.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".