Developing a temperature-dependent Kersten function for soil thermal conductivity
Bibliographic record
Abstract
This paper describes the development of the Kersten function (Ke), which depends on soil temperature and the degree of saturation. The new Kersten function enables the prediction of thermal conductivities of moist soils also including high temperatures. The eight soils used in this paper represent three distinct textural groups, each having a comparable shape of Kersten function. The soil thermal conductivity is obtained from a linear interpolation between the dryness and saturation states with the Ke as the slope. The new Kersten function is valid when the degree of saturation (Sr) is greater than 0.125 and soil temperature is between 30 and 90°C. At a lower degree of saturation (i.e. 0<Sr<0.125), a linear approximation is applied to Ke. The new Ke function gives particularly good agreement with experimental data for temperatures of 30 and 50°C and for low moisture contents at all temperatures. At higher temperatures (i.e. 70 and 90°C) and moisture contents above the permanent wilting point, generally good or acceptable results were obtained. Copyright © 2000 John Wiley & Sons, Ltd.
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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 | 0.001 | 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) | 0.000 | 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 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".