Validation of Soil Survey Estimates of Saturated Hydraulic Conductivity in Major Soils of Puerto Rico
Bibliographic record
Abstract
Ranges or “classes” of probable saturated hydraulic conductivity values (Ksat) are listed for all soil series in USDA-NRCS Soil Survey reports. Listed values are not measured, but rather estimated from other soil properties using a pedotransfer function (PTF). To validate the PTF, we compared estimated Ksat classes with measured values in various horizons of nine major soil series of Puerto Rico. For each horizon, a minimum of 9 and usually 16 Ksat measurements were made with Guelph permeameters near locations where soil pedons had been thoroughly described. In most horizons, Ksat was log-normally distributed. The ratios of Ksat values corresponding to one geometric standard deviation above and below the mean were usually less than 10, which is the ratio of upper and lower class boundaries in the Ksat classification system. For most horizons, measured Ksat values were distributed among the rated Ksat class and the next higher class, indicating that the PTF systematically underestimated the Ksat distributions, but by less than an order of magnitude. From the point of view of soil and water management decisions requiring conservative Ksat estimates, the PTF estimates appeared reasonably conservative without deviating from actual values so as to limit the usefulness of the estimates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".