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Record W3176414285 · doi:10.1016/j.mex.2021.101424

Development of BAS2 for determination of evaporative fluxes

2021· article· en· W3176414285 on OpenAlexafffund
Jared Suchan, Shahid Azam

Bibliographic record

VenueMethodsX · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsModular designAtmosphere (unit)Environmental scienceEvaporative coolerCalibrationComputer scienceFabricationProcess engineeringRange (aeronautics)SimulationSystems engineeringAerospace engineeringEngineeringMechanical engineeringMeteorology

Abstract

fetched live from OpenAlex

Accurate determination of evaporative flux from water surfaces and liquid containing porous media is critical for geotechnical and geoenvironmental applications. Laboratory simulations can isolate the various parameters influencing evaporative fluxes. However, most simulators capture selected surface and atmospheric conditions, and published literature generally provide limited information on the development and operation of the instruments. The new simulator adequately captures a wide range of relevant field parameters, maintains controlled conditions over the required testing time, utilizes readily available components for modular fabrication, and facilitates operational efficiency between individual modules.•This paper presents the modified Bench-Scale Atmosphere Simulator (BAS2).•This paper summarizes various atmosphere simulators developed over the last 25 years.•This paper describes the design, fabrication, operation, calibration, and validation of BAS2.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.111
GPT teacher head0.343
Teacher spread0.232 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations4
Published2021
Admission routes2
Has abstractyes

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