Distances of the TeV supernova remnant complex CTB 37 towards the Galactic bar
Bibliographic record
Abstract
Three supernova remnants (SNRs) form the CTB 37 complex: CTB 37A (G348.5+0.1, associated with the TeV γ-ray source HESS J1714−385), CTB 37B (G348.7+0.3, associated with HESS J1713−381 and the magnetar CXOU J171405.7.381031) and G348.5−0.0. We use 21-cm H i absorption measurements to constrain kinematic distances to these SNRs, which have not previously been determined well. We revise the kinematic distance for CTB 37A to be in the range 6.3–9.5 kpc (previously ∼11.3 kpc) because it is beyond the near 3-kpc arm and in front of the far side of the CO cloud at −145 km s−1 towards l= 348.5. G348.5−0.0 has an H i column density (∼6.1×1021 cm−2) lower than CTB 37A (∼7.1 × 1021 cm−2). Also, G348.5−0.0 does not have the major absorption feature at −107 km s−1 that CTB 37A shows. This is caused by the near 3-kpc arm, so G348.5−0.0 is at a distance of ≤6.3 kpc. CTB 37B is at a distance of ∼13.2 kpc (previously 5–9 kpc) based on: (1) it has an absorption feature at −10 ± 5 km s−1 from the far 3-kpc arm, so CTB 37B is behind it; (2) there is absorption at −30 km s−1 but not at −26 km s−1, which yields the distance value; and (3) the H i column density towards CTB 37B (∼8.3 × 1021 cm−2) is larger than that towards CTB 37A. In summary, CTB 37A, CTB 37B and G348.5+0.0 are all at different distances and are only by chance nearby each other on the sky. In addition, we conclude that CTB 37A and 37B are not associated with the historical supernova AD 393.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".