Herschel Gould Belt Survey Observations of Dense Cores in the Cepheus Flare Clouds
Bibliographic record
Abstract
Abstract We present Herschel SPIRE and PACS maps of the Cepheus Flare clouds L1157, L1172, L1228, L1241, and L1251, observed by the Herschel Gould Belt Survey of nearby star-forming molecular clouds. Through modified blackbody fits to the SPIRE and PACS data, we determine typical cloud column densities of (0.5–1.0) × 1021 cm−2 and typical cloud temperatures of 14–15 K. Using the getsources identification algorithm, we extract 832 dense cores from the SPIRE and PACS data at 160–500 μm. From placement in a mass versus size diagram, we consider 303 to be candidate prestellar cores, and 178 of these to be “robust” prestellar cores. From an independent extraction of sources at 70 μm, we consider 25 of the 832 dense cores to be protostellar. The distribution of background column densities coincident with candidate prestellar cores peaks at (2–4) × 1021 cm−2. About half of the candidate prestellar cores in Cepheus may have formed as a result of the widespread fragmentation expected to occur within filaments of “transcritical” line mass. The lognormal robust prestellar core mass function (CMF) drawn from all five Cepheus clouds peaks at 0.56 M ⊙ and has a width of ∼0.5 dex, similar to that of Aquila’s CMF. Indeed, the width of Cepheus’s aggregate CMF is similar to the stellar system initial mass function (IMF). The similarity of CMF widths in different clouds and the system IMF suggests a common, possibly turbulent origin for seeding the fluctuations that evolve into prestellar cores and stars.
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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 | 0.001 | 0.001 |
| 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".