THE BOLOCAM GALACTIC PLANE SURVEY. XII. DISTANCE CATALOG EXPANSION USING KINEMATIC ISOLATION OF DENSE MOLECULAR CLOUD STRUCTURES WITH<sup>13</sup>CO(1-0)
Bibliographic record
Abstract
We present an expanded distance catalog for 1710 molecular cloud structures identified in the Bolocam Galactic Plane Survey (BGPS) version 2, representing a nearly threefold increase over the previous BGPS distance catalog. We additionally present a new method for incorporating extant data sets into our Bayesian distance probability density function (DPDF) methodology. To augment the dense-gas tracers (e.g., HCO (3–2), NH 3 (1,1)) used to derive line-of-sight velocities for kinematic distances, we utilize the Galactic Ring Survey (GRS) 13 CO(1–0) data to morphologically extract velocities for BGPS sources. The outline of a BGPS source is used to select a region of the GRS 13 CO data, along with a reference region to subtract enveloping diffuse emission, to produce a line profile of 13 CO matched to the BGPS source. For objects with a HCO (3–2) velocity, ≈95% of the new 13 CO(1–0) velocities agree with that of the dense gas. A new prior DPDF for kinematic distance ambiguity (KDA) resolution, based on a validated formalism for associating molecular cloud structures with known objects from the literature, is presented. We demonstrate this prior using catalogs of masers with trigonometric parallaxes and H ii regions with robust KDA resolutions. The distance catalog presented here contains well-constrained distance estimates for 20% of BGPS V2 sources, with typical distance uncertainties ≲ 0.5 kpc. Approximately 75% of the well-constrained sources lie within 6 kpc of the Sun, concentrated in the Scutum–Centaurus arm. Galactocentric positions of objects additionally trace out portions of the Sagittarius, Perseus, and Outer arms in the first and second Galactic quadrants, and we also find evidence for significant regions of interarm dense gas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".