FILAMENTARY STAR FORMATION: OBSERVING THE EVOLUTION TOWARD FLATTENED ENVELOPES
Bibliographic record
Abstract
Filamentary structures are ubiquitous from large-scale molecular clouds (a few parsecs) to small-scale circumstellar envelopes around Class 0 sources (∼1000 AU to ∼0.1 pc). In particular, recent observations with the Herschel Space Observatory emphasize the importance of large-scale filaments (a few parsecs) and star formation. The small-scale flattened envelopes around Class 0 sources are reminiscent of the large-scale filaments. We propose an observationally derived scenario for filamentary star formation that describes the evolution of filaments as part of the process for formation of cores and circumstellar envelopes. If such a scenario is correct, small-scale filamentary structures (0.1 pc in length) with higher densities embedded in starless cores should exist, although to date almost all the interferometers have failed to observe such structures. We perform synthetic observations of filaments at the prestellar stage by modeling the known Class 0 flattened envelope in L1157 using both the Combined Array for Research in Millimeter-wave Astronomy (CARMA) and the Atacama Large Millimeter/Submillimeter Array (ALMA). We show that with reasonable estimates for the column density through the flattened envelope, the CARMA D array at 3 mm wavelengths is not able to detect such filamentary structure, so previous studies would not have detected them. However, the substructures may be detected with the CARMA D+E array at 3 mm and the CARMA E array at 1 mm as a result of more appropriate resolution and sensitivity. ALMA is also capable of detecting the substructures and showing the structures in detail compared to the CARMA results with its unprecedented sensitivity. Such detection will confirm the new proposed paradigm of non-spherical star formation.
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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 | 0.000 |
| 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) | 0.000 | 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".