Deuterium Fractionation in the Oph-H-MM1 Dense Core of the L1688 Low Mass Star-Forming Region
Bibliographic record
Abstract
Molecular clouds fragment to form dense cores, which are the first stage of star formation. Such objects are cold, with temperature of ~10 K and density of $${{10}^{4}}{-} {{10}^{7}}$$ cm–3, with predominance of thermal motions and high deuterium fraction. These objects give us information about the initial conditions of star formation and thus they are very important to understand this process. High abundance of deuterated species indicates that a dense core is close to the onset of star formation. In this work, we study deuterium fractionation, which occurs due to chemical reactions that take place under cold core conditions. To measure deuterium fraction, we use nitrogen-bearing species, because they stay longer in the gas phase at low temperatures. We choose the L1688 low-mass star-forming region as one of the closest ones, containing a large number of cold dense cores. We use spectral maps of two lines, N2H+(1–0) and N2D+(1–0), towards one of the dense cores in L1688, Oph-H-MM1, observed with the IRAM 30 m telescope. We measure column densities of N2D+ and N2H+ and deuterium fraction as the ratio of column densities. The map shows an increase in deuterium fraction towards the core center, which is consistent with theoretical predictions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".