ALMA-IMF. IX. Catalog and Physical Properties of 315 SiO Outflow Candidates in 15 Massive Protoclusters
Bibliographic record
Abstract
Abstract We present a catalog of 315 protostellar outflow candidates detected in SiO J = 5 − 4 in the ALMA-IMF Large Program, observed with ∼2000 au spatial resolution, 0.339 km s−1 velocity resolution, and 2–12 mJy beam−1 (0.18–0.8 K) sensitivity. We find median outflow masses, momenta, and kinetic energies of ∼0.3 M ⊙, 4 M ⊙ km s−1, and 1045 erg, respectively. Median outflow lifetimes are 6000 yr, yielding median mass, momentum, and energy rates of M ̇ = 10−4.4 M ⊙ yr−1, P ̇ = 10−3.2 M ⊙ km s−1 yr−1, and E ̇ = 1 L ⊙. We analyze these outflow properties in the aggregate in each field. We find correlations between field-aggregated SiO outflow properties and total mass in cores (∼3σ–5σ), and no correlations above 3σ with clump mass, clump luminosity, or clump luminosity-to-mass ratio. We perform a linear regression analysis and find that the correlation between field-aggregated outflow mass and total clump mass—which has been previously described in the literature—may actually be mediated by the relationship between outflow mass and total mass in cores. We also find that the most massive SiO outflow in each field is typically responsible for only 15%–30% of the total outflow mass (60% upper limit). Our data agree well with the established mechanical force−bolometric luminosity relationship in the literature, and our data extend this relationship up to L ≥ 106 L ⊙ and P ̇ ≥ 1 M ⊙ km s−1 yr−1. Our lack of correlation with clump L/M is inconsistent with models of protocluster formation in which all protostars start forming at the same time.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".