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Record W1965115805 · doi:10.13031/2013.32600

Nebraska Water and Energy Flux Measurement, Modeling, and Research Network (NEBFLUX)

2010· article· en· W1965115805 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTransactions of the ASABE · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsFluxNetEnvironmental scienceMicroclimateEcosystemBiosphereWater vaporAtmospheric sciencesEnergy fluxWater cycleVegetation (pathology)Terrestrial ecosystemEddy covarianceEcologyHydrology (agriculture)GeographyMeteorologyEngineering

Abstract

fetched live from OpenAlex

Surface energy and water vapor fluxes play a critical role in understanding the response of agro-ecosystems to changes in environmental and atmospheric parameters. These fluxes play a crucial role in exploring the dynamics of water and energy use efficiencies of these systems. Quantification of the fluxes is also necessary for assessing the impact of land use and management changes on water balances. Accomplishing these goals requires measurement of water vapor and energy exchanges between various vegetation surfaces and microclimates for long-enough periods to understand the behavior and dynamics involved with the flux transfer so that robust models can be developed to predict these processes under different scenarios. Networks of flux towers such as AMERIFLUX, FLUXNET, FLUXNET-CANADA, EUROFLUX, ASIAFLUX, and CAR-BOEUROPE have been collecting data on exchange processes between biosphere and atmosphere for multiple years across the globe to better understand the functioning of terrestrial ecosystems and their role in regional and/or continental and global carbon, water, and energy cycles, providing a unique service to the scientific community. Nonetheless, there is an imperative need for these kinds of networks to increase in number and intensity due to the great diversity among ecosystems and agro-ecosystems in species composition, physiological properties, physical structure, microclimatic and climatic conditions, and management practices. The Nebraska Water and Energy Flux Measurement, Modeling, and Research Network (NEBFLUX) is a comprehensive network that is designed to measure surface energy and water vapor fluxes, microclimatic variables, plant physiological parameters, soil water content, surface characteristics, and their interactions for various vegetation surfaces. The NEBFLUX is a network of micrometeorological tower sites that uses mainly Bowen ratio energy balance systems (BREBS) to measure surface water vapor and energy fluxes between terrestrial agro-ecosystems and microclimate. At present, ten BREBSs and one eddy covariance system are operating on a long-term and continuous basis for vegetation surfaces ranging from tilled and untilled irrigated and rainfed croplands, irrigated and rainfed grasslands, alfalfa, to Phragmites (Phragmites australis)-dominated cottonwood (Populus deltoides var. occidentalis) and willow stand (Willow salix) plant communities. The NEBFLUX project will provide good-quality flux and other extensive supportive data on plant physiology [leaf area index, stomatal resistance, within-canopy radiation parameters, productivity (yield and/or biomass), and plant height], soil characteristics, soil water content, and surface characteristics to the micrometeorology, water resources and agricultural engineering, and science community on broad spectrum of agro-ecosystems. The fundamental premise of the NEBFLUX project is to measure continuous and long-term (at least ten complete annual cycles for each surface) exchange of water vapor and energy fluxes. In addition to the scientific and research objectives, information dissemination to educate the general public and youth is another important objective and output of the network. This article describes the specific goals and objectives, basic principles, and operational characteristics of the NEBFLUX.

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.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.229
Teacher spread0.206 · 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