Diviner Lunar Radiometer Observations of Cold Traps in the Moon’s South Polar Region
Bibliographic record
Abstract
Watering the Moon About a year ago, a spent upper stage of an Atlas rocket was deliberately crashed into a crater at the south pole of the Moon, ejecting a plume of debris, dust, and vapor. The goal of this event, the Lunar Crater Observation and Sensing Satellite (LCROSS) experiment, was to search for water and other volatiles in the soil of one of the coldest places on the Moon: the permanently shadowed region within the Cabeus crater. Using ultraviolet, visible, and near-infrared spectroscopy data from accompanying craft, Colaprete et al. (p. 463 ; see the news story by Kerr ; see the cover) found evidence for the presence of water and other volatiles within the ejecta cloud. Schultz et al. (p. 468 ) monitored the different stages of the impact and the resulting plume. Gladstone et al. (p. 472 ), using an ultraviolet spectrograph onboard the Lunar Reconnaissance Orbiter (LRO), detected H 2 , CO, Ca, Hg, and Mg in the impact plume, and Hayne et al. (p. 477 ) measured the thermal signature of the impact and discovered that it had heated a 30 to 200 square-meter region from ∼40 kelvin to at least 950 kelvin. Paige et al. (p. 479) mapped cryogenic zones predictive of volatile entrapment, and Mitrofanov et al. (p. 483 ) used LRO instruments to confirm that surface temperatures in the south polar region persist even in sunlight. In all, about 155 kilograms of water vapor was emitted during the impact; meanwhile, the LRO continues to orbit the Moon, sending back a stream of data to help us understand the evolution of its complex surface structures.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".