H <sub>2</sub> O at the Phoenix Landing Site
Bibliographic record
Abstract
Phoenix Ascending The Phoenix mission landed on Mars in March 2008 with the goal of studying the ice-rich soil of the planet's northern arctic region. Phoenix included a robotic arm, with a camera attached to it, with the capacity to excavate through the soil to the ice layer beneath it, scoop up soil and water ice samples, and deliver them to a combination of other instruments—including a wet chemistry lab and a high-temperature oven combined with a mass spectrometer—for chemical and geological analysis. Using this setup, Smith et al. (p. 58 ) found a layer of ice at depths of 5 to 15 centimeters, Boynton et al. (p. 61 ) found evidence for the presence of calcium carbonate in the soil, and Hecht et al. (p. 64 ) found that most of the soluble chlorine at the surface is in the form of perchlorate. Together these results suggest that the soil at the Phoenix landing site must have suffered alteration through the action of liquid water in geologically the recent past. The analysis revealed an alkaline environment, in contrast to that found by the Mars Exploration Rovers, indicating that many different environments have existed on Mars. Phoenix also carried a lidar, an instrument that sends laser light upward into the atmosphere and detects the light scattered back by clouds and dust. An analysis of the data by Whiteway et al. (p. 68 ) showed that clouds of ice crystals that precipitated back to the surface formed on a daily basis, providing a mechanism to place ice at the surface.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".