Bibliographic record
Abstract
ABSTRACT We present a catalog of 1964 isolated, compact neutral hydrogen clouds from the Galactic Arecibo L-Band Feed Array Survey Data Release One. The clouds were identified by a custom machine-vision algorithm utilizing the difference of Gaussian kernels to search for clouds smaller than 20′. The clouds have velocities typically between |V LSR| =20 and 400 km s−1, line widths of 2.5–35 km s−1, and column densities ranging from 1 to 35 × 1018 cm−2. The distances to the clouds in this catalog may cover several orders of magnitude, so the masses may range from less than a solar mass for clouds within the Galactic disk, to greater than 104 M ☉ for high-velocity clouds (HVCs) at the tip of the Magellanic Stream. To search for trends, we separate the catalog into five populations based on position, velocity, and line width: HVCs; galaxy candidates; cold low-velocity clouds (LVCs); warm, low positive-velocity clouds in the third Galactic quadrant; and the remaining warm LVCs. The observed HVCs are found to be associated with previously identified HVC complexes. We do not observe a large population of isolated clouds at high velocities as some models predict. We see evidence for distinct histories at low velocities in detecting populations of clouds corotating with the Galactic disk and a set of clouds that is not corotating.
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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 | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".