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Record W2026234892 · doi:10.1117/12.620269

New USDA UVB synthetic spectra algorithm

2005· article· en· W2026234892 on OpenAlexaboutno aff
John M. Davis, James R. Slusser

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsRadiometerAlgorithmSpectral lineComputer scienceRemote sensingZenithEnvironmental scienceUltravioletIrradianceIntegrating sphereSpectral resolutionPhysicsOpticsGeology

Abstract

fetched live from OpenAlex

The US Department of Agriculture's (USDA), UVB Radiation Monitoring and Research Program 1 makes routine measurements of ultraviolet radiation at over 30 sites in the United States, Canada and New Zealand. UV measurements of total, direct and diffuse horizontal irradiances, in seven spectral channels at two nm nominal bandwidths are made with a Yankee Scientific Inc., Multiple Filter Rotating Shadow band Radiometer (UV MFRSR). A similar instrument takes measurements in the visible region with 10 nm bandwidths. The UVB group has provided, upon request, a high resolution UV product referred to as spectra, based on application of a non-linear estimation method described in Min and Harrison 2 (1998) to UV MFRSR data. This presentation examines typical problems encountered when the synthetic spectra algorithm is applied to data collected at large solar zenith angles and when the application is extended to spectral regions beyond 368 nm, the center of the longest wavelength UV MFRSR channel. In particular, the effects on derived products such as the Caldwell or Flint 3 action spectra are discussed. The useful spectral region of the algorithm has been expanded by including one or more of the datum from the visible MFRSR. This extension properly constrains the derived spectrum beyond 368 nm providing especially improved Flint action values, and can be used to estimate a PAR value if extended to include the 862 nm measurement. The extent of disagreement between measurements from LICOR PAR sensors and 'synthetic PAR' values will be presented. Planning for the next version of the synthetic spectra algorithm on the new USDA UVB web site is discussed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.831
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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.

Study designBench or experimental
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

Citations4
Published2005
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicCalibration and Measurement TechniquesFrench-language works237,207