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Record W1963966162 · doi:10.1029/2009je003444

Initial analysis of air temperature and related data from the Phoenix MET station and their use in estimating turbulent heat fluxes

2010· article· en· W1963966162 on OpenAlexaff
Richard Davy, Jeffrey A. Davis, Peter A. Taylor, Carlos F. Lange, Wensong Weng, Jim Whiteway, Haraldur P. Gunnlaugson

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of AlbertaYork University
Fundersnot available
KeywordsPhoenixDaytimeDeckEnvironmental scienceAtmospheric sciencesThermocoupleTurbulenceMeteorologyDiurnal cycleAir temperatureDiurnal temperature variationClimatologyGeologyMaterials scienceGeography

Abstract

fetched live from OpenAlex

Thermocouples at three levels on a 1 m mast on the deck of the Phoenix Lander provided temperature data throughout the 151 sol Phoenix mission. Air temperatures showed a large diurnal cycle which showed little sol to sol variation, especially over the first 90 sols of the mission. Daytime temperatures at the top (2 m) level typically rose to about 243 K (−30°C) in early afternoon and had large (10°) turbulent fluctuations. These are analyzed and used to estimate heat fluxes. Late afternoon conditions were relatively calm with minimal temperature fluctuations but CFD computations show that heating from the lander deck and instruments have influenced temperatures measured at the lowest level (0.25 m above the deck) on the mast.

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)0.001
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.047
GPT teacher head0.332
Teacher spread0.285 · 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

Citations75
Published2010
Admission routes1
Has abstractyes

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