Modeling soil thermal conductivities over a wide range of conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it