The association of IRAS sources and $\mathsf{^{12}}$CO emission inthe outer Galaxy
Bibliographic record
Abstract
We have revisited the question of the association of CO emission with IRAS sources in the outer Galaxy using data from the FCRAO Outer Galaxy Survey (OGS). The availability of a large-scale high-resolution CO survey allows us to approach the question of IRAS-CO associations from a new direction – namely we examined all of the IRAS sources within the OGS region for associated molecular material. By investigating the association of molecular material with random lines of sight in the OGS region we were able to construct a quantitative means to judge the likelihood that any given IRAS-CO association is valid and to disentangle multiple emission components along the line of sight. The paper presents a list of all of the IRAS-CO associations in the OGS region. We show that, within the OGS region, there is a significant increase (~22%) in the number of probable star forming regions over previous targeted CO surveys towards IRAS sources. As a demonstration of the utility of the IRAS-CO association table we present the results of three brief studies on candidate zone-of-avoidance galaxies with IRAS counterparts, far outer Galaxy CO clouds, and very bright CO clouds with no associated IRAS sources. We find that ~25% of such candidate ZOAGs are Galactic objects. We have discovered two new far outer Galaxy star-forming regions, and have discovered six bright molecular clouds that we believe are ideal targets for the investigation of the earliest stages of sequential star formation around Hii regions. Finally, this paper provides readers with the necessary data to compare other catalogued data sets with the OGS data.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".