THERMAL CONDUCTIVITY OF OTTAWA SAND PARTIALLY AND TOTALLY SATURATED WITH WATER
Bibliographic record
Abstract
Ottawa sand is a widely studied material in as much its properties are well known, and so it is particularly suited to be used as reference material to develop new analysis methods. This is the reason why it has been chosen to investigate thermal conductivity of partially saturated with water porous media with the probe method. To this goal a special probe developed by the authors’ laboratory has been used, whose accuracy had been established during previous tests as 1.5 %. \nThermal conductivity of Ottawa sand has been measured in three different states: dry, totally saturated with water, and saturated to 50%. In all conditions values were measured as a function of temperature from –20 °C to 80°C. A special procedure has been studied and tested in order to get best uniformity of water distribution in the material. \nMany measurements have been repeated supplying different electric power to the probe, in order to vary the temperature increase. The aim of this action is to recognize a possible influence of phase change, due to the power supplied for the test procedure itself, during measurements. \nResults show a typical behaviour of thermal conductivity versus temperature, intermediate between the solid phase and fluid one. Also a characteristic behaviour versus temperature increase is evident in single tests, due to different phenomena occurred in the three phases porous media.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".