Hydrometeorological observations at three boreal forest sites (aspen, jack pine, and black spruce) located in central Saskatchewan, Canada
Bibliographic record
Abstract
Long-term observations are presented here from two coniferous (jack pine and black spruce) and one deciduous (aspen) forest sites located in central Saskatchewan, Canada. These sites were initiated through the Boreal Ecosystem and Atmosphere Study (BOREAS) program during 1994-96 (http://boreas.gsfc.nasa.gov/) and were later operated under the Boreal Ecosystem Research and Monitoring Sites (BERMS) program. All three sites were equipped with rich instrumentation that include walk-up scaffold towers fitted with sensors to measure air temperature, humidity and wind speed, above canopy shortwave and longwave radiation components, as well as fluxes of energy, carbon and water. Other onsite measurements included precipitation, snow depth, snow density, snow temperature, soil temperature and moisture profiles. These observations are useful for an improved understanding about the contrasts among sites. Moreover, the data is also very useful for modelling applications (calibration and validation). In addition to site observations, dynamically downscaled future meteorological observations by the Weather Research Forecast (WRF) model using Pseudo Global Warming (PGW) approach are included in the dataset. The WRF data was biased corrected by quantile-mapping method using the observed dataset. Thus, the data is ideal for testing, development, calibration, improvement, and validation of hydrological and/or land surface models as well as for projecting future changes in critical processes under changing climate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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 teacher head, 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".