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Record W2061302463 · doi:10.1029/2009je003422

On pressure measurement and seasonal pressure variations during the Phoenix mission

2010· article· en· W2061302463 on OpenAlexaff
Peter A. Taylor, Henrik Kahanpää, Wensong Weng, Ayodeji Akingunola, C. Cook, C. Dickinson, Ari‐Matti Harri, Darren Hill, V. Hipkin, Jouni Polkko, Jim Whiteway

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsCanadian Space AgencyYork University
Fundersnot available
KeywordsPhoenixMars Exploration ProgramEnvironmental sciencePressure sensorCalibrationPressure measurementMeteorologyPhysicsMathematicsGeographyStatistics

Abstract

fetched live from OpenAlex

In situ surface pressures measured at 2 s intervals during the 150 sol Phoenix mission are presented and seasonal variations discussed. The lightweight Barocap®/Thermocap® pressure sensor system performed moderately well. However, the original data processing routine had problems because the thermal environment of the sensor was subject to more rapid variations than had been expected. Hence, the data processing routine was updated after Phoenix landed. Further evaluation and the development of a correction are needed since the temperature dependences of the Barocap sensor heads have drifted after the calibration of the sensor. The inaccuracy caused by this appears when the temperature of the unit rises above 0°C. This frequently affects data in the afternoons and precludes a full study of diurnal pressure variations at this time. Short‐term fluctuations, on time scales of order 20 s are unaffected and are reported in a separate paper in this issue. Seasonal variations are not significantly affected by this problem and show general agreement with previous measurements from Mars. During the 151 sol mission the surface pressure dropped from around 860 Pa to a minimum (daily average) of 724 Pa on sol 140 (Ls 143). This local minimum occurred several sols earlier than expected based on GCM studies and Viking data. Since battery power was lost on sol 151 we are not sure if the timing of the minimum that we saw could have been advanced by a low‐pressure meteorological event. On sol 95 (Ls 122), we also saw a relatively low‐pressure feature. This was accompanied by a large number of vertical vortex events, characterized by short, localized (in time), low‐pressure perturbations.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.030
GPT teacher head0.293
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations55
Published2010
Admission routes1
Has abstractyes

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