A Core Mass Function Indistinguishable from the Salpeter Stellar Initial Mass Function Using 1000 au Resolution ALMA Observations
Bibliographic record
Abstract
Abstract We present the core mass function (CMF) of the massive star-forming clump G33.92 + 0.11 using 1.3 mm observations obtained with the Atacama Large Millimeter/submillimeter Array (ALMA). With a resolution of 1000 au, this is one of the highest resolution CMF measurements to date. The CMF is corrected by flux and number incompleteness to obtain a sample that is complete for gas masses M ≳ 2.0 M ⊙. The resulting CMF is well represented by a power-law function ( dN / d log M ∝ M Γ ), whose slope is determined using two different approaches: (i) by least-squares fitting of power-law functions to the flux- and number-corrected CMF, and (ii) by comparing the observed CMF to simulated samples with similar incompleteness. We provide a prescription to quantify and correct a flattening bias affecting the slope fits in the first approach, which is caused by small-sample or edge effects when the data are represented by either classical histograms or a kernel density estimate, respectively. The resulting slopes from both approaches are in good agreement each other, with Γ = − 1.11 − 0.11 + 0.12 being our adopted value. Although this slope appears to be slightly flatter than the Salpeter slope Γ = −1.35 for the stellar initial mass function (IMF), we find from Monte Carlo simulations that the CMF in G33.92 + 0.11 is statistically indistinguishable from the Salpeter representation of the stellar IMF. Our results are consistent with the idea that the form of the IMF is inherited from the CMF, at least at high masses and when the latter is observed at high enough resolution.
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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 | 0.001 | 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".