Consolidated surface moisture budget measurements from high-latitude flux tower sites at daily, weekly, and monthly time periods, 1995-2019.
Bibliographic record
Abstract
This dataset contains in situ measurements of the atmosphere-surface moisture fluxes (precipitation, evapotranspiration) and the associated atmospheric drivers of evapotranspiration at 45 terrestrial sites in northern high latitudes. For each site, the raw measurements for 30-minute periods have been aggregated into daily, weekly and monthly averages of the atmospheric variables and daily totals of precipitation (P) and evapotranspiration (ET). The dataset is intended to facilitate diagnostic studies of the variations of the surface moisture balance over timescales of days to seasons. All sites have at least 3 years of data and are distributed as follows: Canada (10), Alaska (17), Russia (8), Finland (2), Sweden (3), Svalbard (1), Greenland (3), Iceland (1). Atmospheric variables include air temperature (2-meter), relative humidity, wind speed, sensible heat flux, ground heat flux, net shortwave radiation and net longwave radiation. Useful data are generally limited to the warm season (April/May through September/October). An auxiliary file includes the key descriptors for each site: AmeriFlux/FluxNet site name and identifier, latitude-longitude, years of data coverage, dominant vegetation type, and the presence or absence of permafrost.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.019 |
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.
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".