DEEP<i>K<sub>s</sub></i>-NEAR-INFRARED SURFACE PHOTOMETRY OF 80 DWARF IRREGULAR GALAXIES IN THE LOCAL VOLUME
Bibliographic record
Abstract
We present deep near-infrared (K_s) images and surface photometry for 80 dwarf irregular galaxies (dIs) within ~5 Mpc of the Milky Way. The galaxy images were obtained at five different facilities between 2004 and 2006. The image reductions and surface photometry have been performed using methods specifically designed for isolating faint galaxies from the high and varying near-infrared sky level. Fifty-four of the 80 dIs have surface brightness profiles which could be fit to a hyperbolic-secant (sech) function, while the remaining profiles could be fit to the sum of a sech and a Gaussian function. From these fits, we have measured central surface brightnesses, scale lengths, and integrated magnitudes. This survey is part of a larger study of the connection between large-scale structure and the global properties of dIs, the hypothesized building-blocks of more massive galaxies.
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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 | 0.001 | 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) | 0.001 | 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".