The Distribution of Ortho–H<sub>2</sub>D<sup>+</sup>(1<sub>1,0</sub>–1<sub>1,1</sub>) in L1544: Tracing the Deuteration Factory in Prestellar Cores
Bibliographic record
Abstract
Prestellar cores are unique laboratories for studying the chemical and physical conditions preceding star formation. We observed the prestellar core L1544 in the fundamental transition of ortho-H 2 D + (1 1,0 -1 1,1 ) at different positions over 100'' and found a strong correlation between its abundance and the CO depletion factor. We also present a tentative detection of the fundamental transition of para-D 2 H + (1 1,0 -1 0,1 ) at the dust emission peak. Maps in N 2 H + , N 2 D + , HCO + , and DCO + are used and interpreted with the aid of a spherically symmetric chemical model that predicts the column densities and abundances of these species as a function of radius. The correlation between the observed deuterium fractionation of H , N 2 H + , and HCO + and the observed integrated CO depletion factor across the core can be reproduced by this chemical model. In addition, a simpler model is used to study the H 2 D + ortho-to-para ratio. We conclude that, in order to reproduce the observed ortho-H 2 D + observations, the grain radius should be larger than 0.3 μm.
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 | 0.000 | 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".