Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Dwarf Galaxy Survey (DGS) program is studying low-metallicity galax- \nies using 230h of far-infrared (FIR) and submillimetre (submm) photometric and \nspectroscopic observations of the Herschel Space Observatory and draws to this \na rich database of a wide range of wavelengths tracing the dust, gas and stars. \nThis sample of 50 galaxies includes the largest metallicity range achievable in the \nlocal Universe including the lowest metallicity (Z) galaxies, 1/50 Z⊙, and spans \n4 orders of magnitude in star formation rates. The survey is designed to get a \nhandle on the physics of the interstellar medium (ISM) of low metallicity dwarf \ngalaxies, especially on their dust and gas properties and the ISM heating and \ncooling processes. The DGS produces PACS and SPIRE maps of low-metallicity \ngalaxies observed at 70, 100, 160, 250, 350, and 500 μm with the highest sensi- \ntivity achievable to date in the FIR and submm. The FIR fine-structure lines, \n[CII] 158μm, [OI] 63μm, [OI] 145μm, [OIII] 88μm, [NIII] 57μm and [NII] 122 \nand 205 μm have also been observed with the aim of studying the gas cooling \nin the neutral and ionized phases. The SPIRE FTS observations include many \nCO lines (J=4-3 to J=13-12), [NII] 205 μm and [CI] lines at 370 and 609 μm. \nThis paper describes the sample selection and global properties of the galaxies, \nthe observing strategy as well as the vast ancillary database available to comple- \nment the Herschel observations. The scientific potential of the full DGS survey \nis described with some example results included.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 it