Validation of Spectral and Broadband UV-B (290- 325 nm)
Bibliographic record
Abstract
Stratospheric ozone depletion, as a result of increasing chlorofluorocarbons in the stratosphere, allows more UV-B irradiance (290- 325 nm) to reach the earth’s surface with possible detrimental biological effects. Be-cause there are few UV-B radiation stations, irradiance models are useful tools for estimating irradiances where measurements are not made. Estimates of spectral and broadband irradiances from a numerical model are compared with Brewer spectrophotometer measurements at nine Canadian stations (Alert, Resolute Bay, Churchill, Edmonton, Regina, Winnipeg, Montreal, Halifax and Toronto) and 26 years of data. The model uses either the discrete ordinate radiative transfer (DISORT) or the delta-Eddington algorithms to solve the radiative transfer equation for a 49-layer, vertically inhomogeneous, plane-parallel atmosphere, with cloud inserted between the 2 and 3 km heights. Spectral calculations are made at 1 nm intervals. The model uses extraterrestrial spectral irradiance, spectral optical properties for each atmospheric layer for ozone, air mole-cules, and aerosol and surface albedo. A fixed broadband cloud optical depth of 27 was satisfactory for cal-culating cloudy sky irradiances at all stations except in the arctic. Comparisons are made both for daily totals and for monthly averaged spectral and broadband irradiances. The delta-Eddington method is shown to be unsuitable for calculating spectral irradiances under clear skies,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".