ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions – XXI. A large-sample observational study of ethanol and dimethyl ether in hot cores
Bibliographic record
Abstract
ABSTRACT Hot cores, as a stage of massive star formation, exhibit abundant line emissions of complex organic molecules (COMs). We present a deep line survey of two isomers of C$_2$H$_6$O: ethanol (C$_2$H$_5$OH; EA), and dimethyl ether (CH$_3$OCH$_3$; DE) as well as their possible precursor CH$_3$OH towards 60 hot cores by using the Atacama Large Millimeter/submillimeter Array (ALMA) 3 mm line observations. EA is detected in 40 hot cores and DE is detected in 59 hot cores. Of these, EA and DE are simultaneously detected in 39 hot cores. We calculate rotation temperatures and column densities of EA and DE by using the eXtended CASA Line Analysis Software Suite (xclass) software. The average rotation temperature of EA is higher than that of DE, whereas the average column density of EA is lower than that of DE. Combined with previous studies of hot cores and hot corinos, we find strong column density correlations among EA and DE ($\rho$ = 0.92), EA and CH$_3$OH ($\rho$ = 0.82), as well as DE and CH$_3$OH ($\rho$ = 0.80). The column density ratios of EA/DE versus the column densities of CH$_3$OH remain nearly constant with values within ~1 order of magnitude. These strong correlations and the stable ratios, suggest that EA, DE, and CH$_3$OH could be chemically linked, with CH$_3$OH potentially serving as a precursor for EA and DE. Compared with chemical models, the three different warm-up time-scale models result in the systematic overproduction of EA and the systematic underproduction of DE. Therefore, our large sample observations can provide crucial constraints on chemical models.
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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 | 0.001 |
| 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) | 0.002 | 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".