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Record W3123439089 · doi:10.1117/12.3099575

USDA UV-B Monitoring and Research Program

2020· article· en· W3123439089 on OpenAlexaboutno aff
Wei Gao, George Janson, Chelsea A. Corr, Maosi Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceIrradiancePhotosynthetically active radiationRadiometerAtmospheric sciencesEnvironmental chemistryRemote sensingGeographyChemistryBiologyBotanyPhysics

Abstract

fetched live from OpenAlex

Solar Ultraviolet (UV) radiation has significant impacts on human health (e.g., skin cancer) and the environment (e.g., agricultural production and plant litter decomposition). Reductions in UV-absorbing stratospheric ozone resulting from climate change and the anthropogenic emission of ozone depleting substances raised concerns regarding future levels of surface UV radiation. Responding to this potential threat, the U.S. Department of Agriculture (USDA) investigated the need for UV monitoring across the U.S. in 1991 and established the UV-B Monitoring and Research Program (UVMRP) headquartered in Natural Resource Ecology Laboratory at Colorado State University later in 1992. The UVMRP is tasked with providing information on the geographical distribution and temporal trends of UV radiation and studying the effects of UV radiation on a wealth of agricultural interests including crop plants, rangelands, and forests. The UVMRP currently consists of 37 climatological monitoring sites and 4 research sites, most of which are distributed across the U.S., with an additional site in Canada and another in New Zealand. Collectively, these sites encompass 20 ecoregions. Each UVMRP site is equipped with four primary irradiance instruments including the: 1) UV MultiFilter Rotating Shadowband Radiometer (UV-MFRSR), 2) visible MFRSR, 3) UVB-1 broadband meter, and 4) Photosynthetically Active Radiation (PAR) sensor. The UV-MFRSR measures total horizontal, diffuse horizontal, and direct normal irradiance at nominal 300, 305, 311, 317, 325, 332, and 368 nm at 2 nm FWHM (full-width half-maximum). The VIS-MFRSR measures the same three irradiance components at nominal SiC, 415, 500, 610, 665, 860, and 940 nm at 10 nm FWHM. PAR and UVB-1 sensors measure broadband irradiances over the 400-700 nm and 280-320 nm ranges, respectively. All these observations are sampled every 15 or 20 seconds and stored as an average value every three minutes. The raw data measurements are processed following a variety of Quality Control (QC) and calibration procedures to ensure the quality of the data. The primary data products (i.e., irradiances) as well as the derived products (e.g., UV Index and weighted daily/hourly sums) are distributed through the UVMRP website (http://uvb.nrel.colostate.edu). In this poster, we present a UV climatology study that explores long-term trends of erythemal irradiance at eight locations across the U.S. derived from 8-11 years of UVMRP measurements.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.057
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0570.019

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 head0.063
GPT teacher head0.331
Teacher spread0.268 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2020
Admission routes1
Has abstractyes

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