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Record W2034723258 · doi:10.1175/2008jtecha1046.1

Errors of Naturally Ventilated Air Temperature Measurements in a Spatial Observation Network

2008· article· en· W2034723258 on OpenAlexaff
Matthias Mauder, R. L. Desjardins, Zhiling Gao, R. van Haarlem

Bibliographic record

VenueJournal of Atmospheric and Oceanic Technology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsShieldsEnvironmental scienceShieldRadiative transferWind speedRadiationRadiation fluxRoot mean squareThermal radiationMeteorologyHeat fluxAir temperatureFlux (metallurgy)Radiative fluxAtmospheric sciencesTemperature measurementRemote sensingPhysicsOpticsGeologyMaterials scienceMechanicsHeat transfer

Abstract

fetched live from OpenAlex

Abstract A spatial network of 25 air temperature sensors was deployed over an area of 3.5 km × 3.5 km of agricultural land, aiming to calculate the sensible heat flux by spatial averaging instead of temporal averaging. Since temperature sensors in naturally ventilated solar radiation shields were used for these measurements, a correction for radiative heating had to be applied. In this study, the approach of Anderson and Baumgartner was adapted to the cube-shaped HOBO solar radiation shields. This semiempirical correction depends on the shield’s area normal to the sun in addition to solar radiation and wind speed. The required correction coefficients, which can be universally applied for this type of shield, were obtained through comparison with fan-aspirated temperature measurements at one site. The root-mean-square error of the HOBO temperature measurements was reduced from 0.49° to 0.15°C after applying this radiation correction.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.261

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.186
Teacher spread0.178 · 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 teacher head, 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

Citations32
Published2008
Admission routes1
Has abstractyes

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