<title>UV-B over Canada measured by Brewer spectrophotometers and estimated from ozone and pyranometer observations</title>
Bibliographic record
Abstract
Routine standard spectral UVB measurements with Brewer spectrophotometers in the Canadian network began in 1989. The time interval of UV measurements militates against reliable detection of long-term changes in UV. To estimate the UV irradiance (at individual wavelengths and spectrally integrated) values prior to 1989 a statistical model has been developed to derive UVB from other variables, which have been measured since the 1960s. These variables include global solar radiation, total ozone, dew point temperature, and snow cover. The model results are demonstrated to be in good agreement with the measurements since 1989. For example, the standard deviations of the difference between monthly values of measured and derived erythemaly weighted UV irradiation is 3.3% for summer months. The major source of error in the model estimates is likely linked to rare occurrences of absorbing aerosols in the atmosphere. Long records of reliable measurements of total ozone, global solar radiation and other parameters made it possible to derive UVB values at three Canadian stations from the mid 1960s. Trends in derived erythemaly weighted UV at two stations (Toronto and Edmonton) are similar to those expected from total ozone trends although the estimated error of the UV trends is more than 2 times larger. However the increase in annual UV at Churchill (59 N) in 1979-1997 was found to be more than twice that expected from the ozone decline. This is a result of long-term changes in snow cover and clouds.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".