Thermal Design and Analysis of the Phoenix Mars Lander Meteorological Instrument
Bibliographic record
Abstract
The Phoenix Mars Lander is scheduled to be launched in August 2007 and will land in the northern Vastitas Borealis region. The lander is equipped with a suite of instruments designed to investigate the mineralogy and geochemistry of the soil and to study the atmosphere. The Canadian Meteorological Instrument (MET) will measure the location and the extent of clouds and the distribution of scatterers in the atmosphere as well as measuring the air temperature and the barometric pressure. The MET will provide Canadian scientists with a unique opportunity to study the Martian atmosphere and enhance our understanding of the planet in key areas of Canadian expertise. The MET instrument is composed of multiple elements in order to fulfil the science objectives. The MET Light Imaging Detection and Ranging (LIDAR) will probe the atmosphere by sending out laser pulses and measuring the backscattered returns. The MET mast that is instrumented with three thermocouples will measure the atmosphere temperature at three different heights and a Tell Tale installed at the tip will measure wind speed and direction. The upper Payload Electronic Box (PEB) will house the MET barometric pressure sensor and the MET main electronics. This paper will describe Canada's participation in the mission, provide details about the instrument, and explain the rationale behind the thermal design. Furthermore, heat balance and transient results from detailed thermal analyses will be presented.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".