PACS and SPIRE photometer maps of M 33: First results of the<i>HERschel</i> M 33 Extended Survey (HERM33ES)
Bibliographic record
Abstract
Context. Within the framework of the HERM33ES key program, we are studying the star forming interstellar medium in the nearby, metal-poor spiral galaxy M 33, exploiting the high resolution and sensitivity of Herschel. Aims. We use PACS and SPIRE maps at 100, 160, 250, 350, and 500 μm wavelength, to study the variation of the spectral energy distributions (SEDs) with galacto-centric distance. Methods. Detailed SED modeling is performed using azimuthally averaged fluxes in elliptical rings of 2 kpc width, out to 8 kpc galacto-centric distance. Simple isothermal and two-component grey body models, with fixed dust emissivity index, are fitted to the SEDs between 24 μm and 500 μm using also MIPS/Spitzer data, to derive first estimates of the dust physical conditions. Results. The far-infrared and submillimeter maps reveal the branched, knotted spiral structure of M 33. An underlying diffuse disk is seen in all SPIRE maps (250–500 μm). Two component fits to the SEDs agree better than isothermal models with the observed, total and radially averaged flux densities. The two component model, with β fixed at 1.5, best fits the global and the radial SEDs. The cold dust component clearly dominates; the relative mass of the warm component is less than 0.3% for all the fits. The temperature of the warm component is not well constrained and is found to be about 60 K ± 10 K. The temperature of the cold component drops significantly from ~24 K in the inner 2 kpc radius to 13 K beyond 6 kpc radial distance, for the best fitting model. The gas-to-dust ratio for β = 1.5, averaged over the galaxy, is higher than the solar value by a factor of 1.5 and is roughly in agreement with the subsolar metallicity of M 33.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".