PISCOeo_pm, a reference evapotranspiration gridded database based on FAO Penman-Monteith in Peru
Bibliographic record
Abstract
Abstract A new FAO Penman-Monteith reference evapotranspiration gridded dataset is introduced, called PISCOeo_pm. PISCOeo_pm has been developed for the 1981–2016 period at ~1 km (0.01°) spatial resolution for the entire continental Peruvian territory. The framework for the development of PISCOeo_pm is based on previously generated gridded data of meteorological subvariables such as air temperature (maximum and minimum), sunshine duration, dew point temperature, and wind speed. Different steps, i.e., (i) quality control, (ii) gap-filling, (iii) homogenization, and (iv) spatial interpolation, were applied to the subvariables. Based on the results of an independent validation, on average, PISCOeo_pm exhibits better precision than three existing gridded products (CRU_TS, TerraClimate, and ERA5-Land) because it presents a predictive capacity above the average observed using daily and monthly data and has a higher spatial resolution. Therefore, PISCOeo_pm is useful for better understanding the terrestrial water and energy balances in Peru as well as for its application in fields such as climatology, hydrology, and agronomy, among others.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".