Modeling soil thermal conductivities over a wide range of conditions
Bibliographic record
Abstract
This paper presents a new method to seamlessly calculate thermal conductivity for various soil conditions, from loose to compact, organic to mineral, fine to coarse textured, frozen to unfrozen, and dry to wet. The soil is considered as a multi-phase system, containing air, water (liquid, ice), and particles finer (organic matter, minerals) and coarser (gravel) than 2 mm. The new method extends the general portability of the earlier Johansen (1975) method, and this generalization was fine-tuned empirically with data from soil, gravel, and peat drawn from recent and older literature, for frozen and unfrozen conditions from –30 to 30 °C, and for variable moisture and bulk density conditions from dry to saturated. Scatter plots between measured conductivity and best-fitted calculations consistently followed a straight 1:1 correspondence, with R2 values generally above 0.90. The new method was then used to re-interpret thermal conductivity data involving wettable and non-wettable soils, in situ field measurements, and snow. Key words: thermal conductivity, soil, quartz, ice, water, air, density, snow.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".